CN112650850A - Wind and cloud satellite remote sensing mapping data management system - Google Patents
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Abstract
The invention discloses a wind and cloud satellite remote sensing surveying and mapping data management system which comprises a data management server, a data extraction module, a data conversion module, a data classification module and a data fusion module, wherein the data extraction module, the data conversion module, the data classification module and the data fusion module are respectively in communication connection with the data management server. The method is connected with different types of databases, receives data files of different file formats, extracts wind cloud satellite remote sensing mapping data from the databases and extracts the wind cloud satellite remote sensing mapping data from the data files, converts the wind cloud satellite remote sensing mapping data extracted by the data extraction module into text data, classifies the text data converted by the data conversion module, and performs data fusion on the text data classified by the data classification module, so that the collection of multi-source wind cloud satellite remote sensing mapping data is realized, the classification accuracy of the wind cloud satellite remote sensing mapping data is enhanced, and the utilization efficiency of later data is improved.
Description
Technical Field
The invention relates to the technical field of data management, in particular to a wind cloud satellite remote sensing mapping data management system.
Background
The wind cloud meteorological satellite is a meteorological satellite developed in 1977 in China, and 3 first generation polar orbit meteorological satellites, namely wind cloud No. 1A, B and C meteorological satellites, are transmitted in sequence in 1988, 1990 and 1999. Two static orbit wind cloud No. 2 meteorological satellites are launched in 1997 and 2000 in turn to form a China meteorological satellite service monitoring system, and the China meteorological satellite service monitoring system becomes a country which has two orbit meteorological satellites in the world after America and Russia and is a crystal which is constantly struggled and innovated in China for more than 30 years.
The existing wind cloud satellite remote sensing mapping data management system has the defects that all data sources are dispersed and the classification is not accurate enough, so that the data utilization rate is low in the actual data application process.
Disclosure of Invention
The invention aims to provide a wind cloud satellite remote sensing mapping data management system, which realizes the collection of multisource wind cloud satellite remote sensing mapping data, enhances the classification accuracy of the wind cloud satellite remote sensing mapping data, and improves the utilization efficiency of later data so as to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme:
wind cloud satellite remote sensing survey and drawing data management system includes:
the data management server is used for ensuring that each module works normally;
the data extraction module is in communication connection with the data management server and is used for connecting with different types of databases, receiving data files in different file formats and extracting wind cloud satellite remote sensing mapping data from the databases and extracting the wind cloud satellite remote sensing mapping data from the data files;
the data conversion module is in communication connection with the data management server and is used for converting the wind cloud satellite remote sensing mapping data extracted by the data extraction module into text data;
the data classification module is in communication connection with the data management server and is used for classifying the text data converted by the data conversion module; and
and the data fusion module is in communication connection with the data management server and is used for performing data fusion on the text data classified by the data classification module.
The wind cloud satellite remote sensing mapping data management system preferably further comprises an updating strategy configuration module, a data updating module and an updating progress monitoring module, wherein the updating strategy configuration module, the data updating module and the updating progress monitoring module are respectively in communication connection with the data management server;
the updating strategy configuration module is used for responding to data updating configuration operation and generating a data updating strategy;
the data updating module is used for updating data according to a data updating strategy generated by the data updating strategy;
the update progress monitoring module is used for monitoring the execution progress of the data update module in real time.
The wind cloud satellite remote sensing surveying and mapping data management system preferably further comprises a data tracing module, the data tracing module is in communication connection with the data management server, and the data tracing module is used for responding to data tracing operation and displaying data sources of the selected data.
The wind cloud satellite remote sensing surveying and mapping data management system preferably further comprises a data quality detection module, wherein the data quality detection module is in communication connection with the data management server, and the data quality monitoring module is used for verifying data at a preset time node.
Preferably, the specific method for classifying and mining the text data converted by the data conversion module by the data classification module comprises the following steps:
s1, establishing keyword libraries with different levels and different categories, and determining text characteristic vectors corresponding to each piece of text data according to the keyword libraries, wherein the total number of keywords contained in the ith piece of text data is niK total categories and m j-th category keywordsijThen the feature vector of the ith text data is [ m ]i1,mi2···,mij···mik]；
S2, classifying the text data based on a hierarchical fuzzy classification method according to the established keyword library of S1, and calculating the membership degree of each text data to each class in the classification process, wherein the membership degree of the ith text data to the jth class
mijExpressing the number of jth keywords contained in the ith text data, and carrying out fuzzy classification on each text data to corresponding classes according to the membership degree;
s3, selecting text data with large membership degree differentiation as reliable individuals, and obtaining a training function through training of a support vector machine;
defining the membership degree differentiation coefficient of the ith text data as follows:
defining a threshold lambda of a differentiation coefficient;
when beta isiWhen the membership degree is more than or equal to lambda, the individual membership degree difference is called to be a reliable individual which is used as training data of the support vector machine;
when beta isiWhen the number is less than lambda, the individual membership degree difference is small, and the individual is an unreliable individual;
and S4, classifying the text data to be classified by adopting a trained support vector machine training function.
Preferably, in the wind cloud satellite remote sensing mapping data management system of the present invention, the support vector machine in S3 is as follows:
selecting a Gaussian kernel function
(xi,yi) Representing training data, xiRepresenting inputs of training data, yiRepresenting the corresponding output, αiRepresenting Lagrange multipliers, wherein n is the number of training data;
take a certain alphajSamples corresponding to > 0
Training a support vector machine to obtain a decision function:
preferably, the specific method for classifying and mining the text data converted by the data conversion module by the data classification module further comprises text preprocessing to obtain a discretized data text.
Preferably, the specific method for classifying and mining the text data converted by the data conversion module by the data classification module further comprises the step of determining keywords contained in different levels and classes of keyword libraries according to the existing text data.
The wind cloud satellite remote sensing mapping data management system preferably further comprises a backup server and a backup module, wherein the backup server is in communication connection with the data management server, and the backup module is used for backing up data of the data management server through the backup server.
Preferably, the method for backing up the data of the data management server by the backup module through the backup server includes:
s21, a first node of a backup period, wherein the backup module obtains RMAN backup data by using an RMAN backup tool and stores the RMAN backup data in a backup server;
and S22, the second node of the backup period obtains the logic backup data by using a logic backup tool on the basis of the RMAN backup data and stores the logic backup data to the backup server.
Compared with the prior art, the invention has the beneficial effects that:
according to the method, the data extraction module is connected with different types of databases and used for receiving data files of different file formats, wind cloud satellite remote sensing mapping data are extracted from the databases and wind cloud satellite remote sensing mapping data are extracted from the data files, the wind cloud satellite remote sensing mapping data extracted by the data extraction module are converted into text data through the data conversion module, the text data converted by the data conversion module are classified through the data classification module, and finally the text data classified by the data classification module are subjected to data fusion through the data fusion module, so that the collection of the multisource wind cloud satellite remote sensing mapping data is realized, the classification accuracy of the wind cloud satellite remote sensing mapping data is enhanced, and the utilization efficiency of later data is improved.
Drawings
FIG. 1 is a schematic block diagram of a wind cloud satellite remote sensing mapping data management system of the present invention;
FIG. 2 is a flowchart of a specific method for classifying and mining text data converted by a data conversion module by a data classification module of the wind cloud satellite remote sensing mapping data management system of the invention;
fig. 3 is a flowchart of a specific method for backing up data of a data management server by a backup module of the wind cloud satellite remote sensing mapping data management system through the backup server.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
Examples
Referring to fig. 1-3, the present invention provides a technical solution:
wind cloud satellite remote sensing survey and drawing data management system includes:
the data management server is used for ensuring that each module works normally;
the data extraction module is in communication connection with the data management server and is used for connecting with different types of databases, receiving data files in different file formats and extracting wind cloud satellite remote sensing mapping data from the databases and extracting the wind cloud satellite remote sensing mapping data from the data files;
the data conversion module is in communication connection with the data management server and is used for converting the wind cloud satellite remote sensing mapping data extracted by the data extraction module into text data;
the data classification module is in communication connection with the data management server and is used for classifying the text data converted by the data conversion module; and
and the data fusion module is in communication connection with the data management server and is used for performing data fusion on the text data classified by the data classification module.
The technical optimization scheme of the invention also comprises an updating strategy configuration module, a data updating module and an updating progress monitoring module, wherein the updating strategy configuration module, the data updating module and the updating progress monitoring module are respectively in communication connection with the data management server;
the updating strategy configuration module is used for responding to data updating configuration operation and generating a data updating strategy;
the data updating module is used for updating data according to a data updating strategy generated by the data updating strategy;
the update progress monitoring module is used for monitoring the execution progress of the data update module in real time.
The data tracing module is in communication connection with the data management server, and is used for responding to data tracing operation and displaying the data source of the selected data.
The technical optimization scheme of the invention further comprises a data quality detection module, wherein the data quality detection module is in communication connection with the data management server, and the data quality monitoring module is used for verifying data at a preset time point.
As a technical optimization scheme of the present invention, the specific method for classifying and mining the text data converted by the data conversion module by the data classification module includes:
s1, establishing keyword libraries with different levels and different categories, and determining text characteristic vectors corresponding to each piece of text data according to the keyword libraries, wherein the total number of keywords contained in the ith piece of text data is niK total categories and m j-th category keywordsijThen the feature vector of the ith text data is [ m ]i1,mi2···,mij···mik]；
S2, classifying the text data based on a hierarchical fuzzy classification method according to the established keyword library of S1, and calculating the membership degree of each text data to each class in the classification process, wherein the membership degree of the ith text data to the jth class
mijExpressing the number of jth keywords contained in the ith text data, and carrying out fuzzy classification on each text data to corresponding classes according to the membership degree;
s3, selecting text data with large membership degree differentiation as reliable individuals, and obtaining a training function through training of a support vector machine;
defining the membership degree differentiation coefficient of the ith text data as follows:
defining a threshold lambda of a differentiation coefficient;
when beta isiWhen the membership degree is more than or equal to lambda, the individual membership degree difference is called to be a reliable individual which is used as training data of the support vector machine;
when beta isiWhen the number is less than lambda, the individual membership degree difference is small, and the individual is an unreliable individual;
and S4, classifying the text data to be classified by adopting a trained support vector machine training function.
As a technical optimization scheme of the present invention, the support vector machine in S3 is as follows:
selecting a Gaussian kernel function
(xi,yi) Representing training data, xiRepresenting inputs of training data, yiRepresenting the corresponding output, αiRepresenting Lagrange multipliers, wherein n is the number of training data;
take a certain alphajSamples corresponding to > 0
Training a support vector machine to obtain a decision function:
as a technical optimization scheme of the present invention, the specific method for classifying and mining the text data converted by the data conversion module by the data classification module further includes text preprocessing to obtain a discretized data text.
As a technical optimization scheme of the present invention, the specific method for classifying and mining the text data converted by the data conversion module by the data classification module further includes determining keywords contained in different classes of keyword libraries at different levels according to the existing text data.
The data management system further comprises a backup server and a backup module, wherein the backup server is in communication connection with the data management server, and the backup module is used for backing up data of the data management server through the backup server.
As a technical optimization scheme of the present invention, a specific method for the backup module to backup the data of the data management server through the backup server includes:
s21, a first node of a backup period, wherein the backup module obtains RMAN backup data by using an RMAN backup tool and stores the RMAN backup data in a backup server;
and S22, the second node of the backup period obtains the logic backup data by using a logic backup tool on the basis of the RMAN backup data and stores the logic backup data to the backup server.
In summary, the data extraction module is connected with different types of databases and used for receiving data files of different file formats, the wind cloud satellite remote sensing mapping data are extracted from the databases and extracted from the data files, the wind cloud satellite remote sensing mapping data extracted by the data extraction module are converted into text data through the data conversion module, the text data converted by the data conversion module are classified through the data classification module, and finally the text data classified by the data classification module are subjected to data fusion through the data fusion module, so that the collection of the multisource wind cloud satellite remote sensing mapping data is realized, the classification accuracy of the wind cloud satellite remote sensing mapping data is enhanced, and the utilization efficiency of the later data is improved.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. Wind cloud satellite remote sensing survey and drawing data management system, its characterized in that includes:
the data management server is used for ensuring that each module works normally;
the data extraction module is in communication connection with the data management server and is used for connecting with different types of databases, receiving data files in different file formats and extracting wind cloud satellite remote sensing mapping data from the databases and extracting the wind cloud satellite remote sensing mapping data from the data files;
the data conversion module is in communication connection with the data management server and is used for converting the wind cloud satellite remote sensing mapping data extracted by the data extraction module into text data;
the data classification module is in communication connection with the data management server and is used for classifying the text data converted by the data conversion module; and
and the data fusion module is in communication connection with the data management server and is used for performing data fusion on the text data classified by the data classification module.
2. The wind and cloud satellite remote sensing mapping data management system of claim 1, wherein: the system also comprises an updating strategy configuration module, a data updating module and an updating progress monitoring module, wherein the updating strategy configuration module, the data updating module and the updating progress monitoring module are respectively in communication connection with the data management server;
the updating strategy configuration module is used for responding to data updating configuration operation and generating a data updating strategy;
the data updating module is used for updating data according to a data updating strategy generated by the data updating strategy;
the update progress monitoring module is used for monitoring the execution progress of the data update module in real time.
3. The wind and cloud satellite remote sensing mapping data management system of claim 1, wherein: the data source tracing system comprises a data management server and a data tracing module, wherein the data management server is used for managing the data source of the selected data, and the data tracing module is used for responding to the data source tracing operation and displaying the data source of the selected data.
4. The wind and cloud satellite remote sensing mapping data management system of claim 1, wherein: the data management system further comprises a data quality detection module, wherein the data quality detection module is in communication connection with the data management server, and the data quality monitoring module is used for verifying data at a preset time point.
5. The wind cloud satellite remote sensing mapping data management system according to claim 1, wherein the specific method for classifying and mining the text data converted by the data conversion module by the data classification module comprises the following steps:
s11, establishing different levels and different categories of keyword libraries, and determining text characteristic vectors corresponding to each text data according to the keyword libraries, wherein the total number of keywords contained in the ith text data is niK total categories and m j-th category keywordsijThen the feature vector of the ith text data is [ m ]i1,mi2···,mij···mik]；
S12, classifying the text data based on a hierarchical fuzzy classification method according to the established keyword library of S1, and calculating the membership degree of each text data to each class in the classification process, wherein the membership degree of the ith text data to the jth class
mijExpressing the number of jth keywords contained in the ith text data, and carrying out fuzzy classification on each text data to corresponding classes according to the membership degree;
s13, selecting text data with large membership degree differentiation as reliable individuals, and obtaining a training function through training of a support vector machine;
defining the membership degree differentiation coefficient of the ith text data as follows:
defining a threshold lambda of a differentiation coefficient;
when beta isiWhen the value is more than or equal to lambda, the individual membership degree difference is called to be large, and the method is reliableIndividuals as training data for a support vector machine;
when beta isiWhen the number is less than lambda, the individual membership degree difference is small, and the individual is an unreliable individual;
and S14, classifying the text data to be classified by adopting a trained support vector machine training function.
6. The wind and cloud satellite remote sensing mapping data management system according to claim 5, wherein: the support vector machine in S13 is as follows:
selecting a Gaussian kernel function
(xi,yi) Representing training data, xiRepresenting inputs of training data, yiRepresenting the corresponding output, αiRepresenting Lagrange multipliers, wherein n is the number of training data;
take a certain alphajSamples corresponding to > 0
Training a support vector machine to obtain a decision function:
7. the wind and cloud satellite remote sensing mapping data management system according to claim 5, wherein: the specific method for classifying and mining the text data converted by the data conversion module by the data classification module further comprises text preprocessing to obtain a discretized data text.
8. The wind and cloud satellite remote sensing mapping data management system of claim 1, wherein: the specific method for classifying and mining the text data converted by the data conversion module by the data classification module further comprises the step of determining keywords contained in different levels and different categories of keyword libraries according to the existing text data.
9. The wind and cloud satellite remote sensing mapping data management system of claim 1, wherein: the data management system further comprises a backup server and a backup module, wherein the backup server is in communication connection with the data management server, and the backup module is used for backing up data of the data management server through the backup server.
10. The wind cloud satellite remote sensing mapping data management system according to claim 9, wherein the specific method for the backup module to backup the data of the data management server through the backup server includes:
s21, a first node of a backup period, wherein the backup module obtains RMAN backup data by using an RMAN backup tool and stores the RMAN backup data in a backup server;
and S22, the second node of the backup period obtains the logic backup data by using a logic backup tool on the basis of the RMAN backup data and stores the logic backup data to the backup server.
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| CN116186319A (en) * | 2022-11-23 | 2023-05-30 | 自然资源部国土卫星遥感应用中心 | Satellite image data archiving management method and system |
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| CN110222180A (en) * | 2019-06-04 | 2019-09-10 | 江南大学 | A kind of classification of text data and information mining method |
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