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    15 March 2022, Volume 8 Issue 2
    TOPOC: AEROSPACE BIG DATA
    Opportunities and challenges of geo-spatial information science from the perspective of big data
    Deren LI, Guo ZHANG, Yonghua JIANG, Xin SHEN, Weiling LIU
    2022, 8(2):  3-14.  doi:10.11959/j.issn.2096-0271.2022012
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    The era of big data has arrived, and it has penetrated every aspect of human life.As the geo-spatial information science spawned by the intersection of earth sciences and information sciences, the advent of the era of big data provides it with richer prosperous data protection, but also brings new challenges in data storage, management, analysis, and mining, and even caused a certain degree of “data explosion”.From the perspective of big data, the bottlenecks and challenges in the four core areas of geographic information systems, smart cities, remote sensing big data, and spatial data mining were sorted out.And it was pointed out that geo-spatial information science can provide more accurate and real-time spatial information frameworks and more intelligent and more efficient information processing methods for geoscience research, serving intelligent cities, smart earth construction, and sustainable development in the era of big data.Moreover, in the era of big data, the development of geo-spatial information science is facing the double test of software and hardware levels.

    Remote sensing satellite big data high-recision integration processing technology
    Xiaolan QIU, Yuxin HU, Songtao SHANGGUAN, Kun FU
    2022, 8(2):  15-27.  doi:10.11959/j.issn.2096-0271.2022013
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    With the rapid development of China’s aerospace information acquisition technology, aerospace data presents the characteristics of large data volume, large number of types, rapid growth and relatively low value density.Remote sensing satellite data is an important part of aerospace big data.How to make use of the scale effect and the complementary advantages of the data of different satellites, so as to improve the processing accuracy and efficiency, is the key problem to be solved in the remote sensing satellite big data processing system.The development history of our country’s remote sensing satellite ground data processing system was reviewed briefly.The core difficulties faced by the ground processing system were pointed out.A high-precision processing technology for remote sensing satellite big data based on stability feature mining was proposed.And a preliminary implementation was given.The method provides a useful reference for the development of our country’s aerospace big data processing system.

    A survey on information extraction technology based on remote sensing big data
    Weiquan LIU, Cheng WANG, Yu ZANG, Qian HU, Shangshu YU, Baiqi LAI
    2022, 8(2):  28-57.  doi:10.11959/j.issn.2096-0271.2022014
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    With the rapid development of remote sensing technology, our country has established a relatively complete space remote sensing and flexible and diverse aerial remote sensing data acquisition system.Remote sensing big data is mainly based on massive remote sensing data, integrating other multi-source remote sensing data, using big data thinking and methods, and discovering knowledge laws and high-value information in massive data.Firstly, the research work of information extraction technology based on remote sensing big data was reviewed in recent years.Secondly, the development history of remote sensing information extraction technology was expounded from three aspects: remote sensing target detection, remote sensing surface object segmentation, and remote sensing change detection.Finally, the information extraction technology based on remote sensing big data was sorted out, summarized and prospected.

    Integration of remote sensing intelligent processing algorithm using container cloud technology
    Zhitao ZHAO, Lijun ZHAO, Zheng ZHANG, Ping TANG
    2022, 8(2):  58-74.  doi:10.11959/j.issn.2096-0271.2022015
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    With the development of cloud computing technology in remote sensing data processing, container cloud technology was applied to remote sensing data processing, remote sensing intelligent processing algorithm image was deployed and storage services were distributed in the computing cluster, shielding complex environmental dependence problems.And management through configuration files was processed forming an overall technical route from development to deployment, which provides an efficient and reliable new scheme for the integration of remote sensing intelligent processing algorithms.Taking several typical remote sensing intelligent algorithms as examples, the efficiency of the scheme in the integrated development and deployment was proved, and the feasibility of the new cloud mode of remote sensing intelligent technology was explored.

    Remote sensing big data from Chinese ocean satellites and its application service
    Jianqiang LIU, Xiaomin YE, Youguo LAN
    2022, 8(2):  75-88.  doi:10.11959/j.issn.2096-0271.2022016
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    The constructions of three series of the Chinese ocean satellite constellations, including ocean color satellites, ocean dynamic environment satellites and ocean monitoring satellites, and the supporting ground application system have been completed.The Chinese ocean series satellites and their development histories, payloads, product system, data acquisition and distribution methods were introduced.The big data characteristics of ocean satellite remote sensing data were analyzed from their data volumes, data types, data timeliness and data values.The basic data set of ocean satellite remote sensing and its typical application in disaster and environmental monitoring and public services were analyzed.

    Analysis of satellite big data requirements in numerical weather prediction
    Hequn YANG, Xiaofeng WANG, Yanqing GAO, Yiwen LU, Bingxin MA, Xinyao WANG
    2022, 8(2):  89-102.  doi:10.11959/j.issn.2096-0271.2022017
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    Multi cooperative satellites can provide multi spectral, multi temporal, multi factor, multi scale and multi-level remote sensing data, which is rich in valuable information for numerical weather prediction (NWP).In order to support earth system seamless fine gridded forecasting service in the future, the application status of satellite observation big data was discussed for numerical weather prediction from the aspects of detection variables, time density, spatial coverage, horizontal and vertical resolution, as well as accuracy and timeliness.At the same time, in order to make satellite big data be highly tolerant with NWP, the challenges and prospects were summarized, such as multi-satellite integrated and consistent processing, all-weather, coupled data assimilation methods, deep integration with artificial intelligence, and interaction between satellite observation and prediction.

    Applications of remote sensing big data in highway transportation
    Shenggu YUAN, Lun LUO, Ronggang GUO, Hengbin MAO, Fang WANG, Hongyue CAI, Heping XIAO
    2022, 8(2):  103-119.  doi:10.11959/j.issn.2096-0271.2022011
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    The rise of remote sensing big data applications had a profound impact on the transportation industry, and has played an active role in transportation planning, construction, management and maintenance and other aspects.Firstly, the connotation and characteristics of traffic remote sensing big data were introduced, and the application status of remote sensing big data was summarized in the field of highway traffic and transportation.Secondly, combined with the relevant work carried out by transportation departments based on remote sensing big data in recent years, the typical applications of remote sensing big data in intelligent extraction and analysis of traffic highway damage, highway construction and planning analysis, and intelligent maintenance of highway were mainly introduced.Finally, the development trend and future prospects of traffic remote sensing big data were prospected.

    Key technologies and application exploration of aerospace big data in the construction of new smart city
    Jingye SHI, Pan LI
    2022, 8(2):  120-133.  doi:10.11959/j.issn.2096-0271.2022018
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    The proposal and development of a new smart city has brought new changes, and also put forward higher requirements for the application of technologies such as aerospace big data.The application value of aerospace big data in the construction of new smart city was analyzed.The key technologies of aerospace big data in the application of new smart city were studied.The typical application scenarios of aerospace big data were shown.And some suggestions on using aerospace big data to promote the construction of new smart city were put forward.

    STUDA
    A semi-supervised learning financial news classification algorithm
    Xiaolong ZHANG, Long ZHI, Jian GAO, Zhongchen MIAO, Yuefeng LIN, Yali XIANG, Yun XIONG
    2022, 8(2):  134-144.  doi:10.11959/j.issn.2096-0271.2022019
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    Classifying financial texts is a common task for identifying financial risks.Traditional financial news classification requires a large number of labeled texts to train the classifier.However, labeling financial news requires not only professional financial background knowledge, but also time-consuming and labor-intensive.In order to reduce the dependence on labeled text, a semi-supervised learning financial text classification algorithm- SSF (semi-supervised learning financial news classification algorithm) was proposed, which uses a consistent training method of supervised learning and unsupervised learning to improve the use of unlabeled data.And unsupervised data augmentation for financial texts was introduced, that is, use specific target data augmentation methods for specific tasks to generate more effective data.Experiments on multiple financial news data sets were conducted to verify that the proposed SSF algorithm has a significant improvement in effectiveness compared with other text classification algorithms.

    Research on auxiliary division method based on convolutional neural network
    Shaolin AO, Yongbin QIN, Ruizhang HUANG, Yanping CHEN, Lijuan LIU, Qinghua ZHENG, Changheng CHEN, Shaofen CHENG
    2022, 8(2):  145-157.  doi:10.11959/j.issn.2096-0271.2022020
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    The court system mainly has two modes: manual designated division and simple random division.The above method cannot achieve automatic matching of persons and cases, and there are drawbacks such as money cases and relationship cases.At present, the research on division method mainly has two difficulties: judge’s representation and case matching.Combining the judge’s historical trial data, the judge’s expertise in the judge’s representation was integrated, and a judge representation method that integrates the quality of the trial was proposed.Then, the abstract semantic feature vectors of different granularities in the case representation and the judge representation were learned through the convolutional neural network, the cosine similarity between the case and the feature vectors of multiple judges was calculated, and vector similarity was used to indicate the matching degree between the case and the judge, the top N judges with high matching value were output as recommended judges for the case.Experiments with real data from a court in Guizhou Province, and the results show that the accuracy of the method for recommending judges is 80% higher than the traditional method.

    APPLICATION
    Design and application of unified big data platform of information system for the 14th National Games of the People’s Republic of China
    Xinbo HUANG
    2022, 8(2):  158-167.  doi:10.11959/j.issn.2096-0271.2022021
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    In order to provide first-class information services for the 14th National Games of the People’s Republic of China, it is of great significance to establish a perfect unified big data platform of information system.At first, the core functionality of unified big data platform was expounded, and the platform technology framework was designed.Then, the key technologies of the platform such as competition private network data aggregation technology, big data distributed micro service architecture, data interaction function and 3D security system were analyzed respectively.Finally, according to the information service of the 14th National Games of the People’s Republic of China and the 11th National Games for Persons Disabilities & the 8th National Special Olympic Games, the People’s Republic of China, the application of unified big data platform was analyzed.

    FORUM
    Legislative background and system of China’s Personal Information Protection Law
    Xiaoyang YU, Bo HE
    2022, 8(2):  168-181.  doi:10.11959/j.issn.2096-0271.2022022
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    The Personal Information Protection Law was deliberated in August, 2021 and officially implemented in November, promoting the establishment of China’s legal system for the protection of personal information.Firstly, the background of the Law was systematically introduced, which has gone through three deliberations and adheres to problem orientation, with distinctive features and great significance.Secondly, the rules of the Law were analyzed, focusing on the scope of the concept of personal information, the basic principles of processing personal information, the basis of legality, the rights and obligations of relevant subjects, the cross-border provision rules, as well as the legal liability.Finally, the development of personal information from indirect protection to direct protection and to comprehensive protection was summarized.

    Construction and practical application of big data development index in China-from the government data and social data fusion perspective
    Mingjun GUO, Qin CHEN, Xiaomi AN, Jiandong WANG, Chengqi YI
    2022, 8(2):  182-192.  doi:10.11959/j.issn.2096-0271.2022023
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    In view of the two deficiencies of the current big data index research, data sources are relatively limited and unable to cover each city, based on the perspective of full data fusion of government data and social data, a big data development index was constructed, which integrates government data with social data and presents the “portrait” of big data of various cities in a panoramic manner from the three dimensions of basic capability, innovative application and comprehensive guarantee.The development level of big data was evaluated objectively, which providing objective data reference for government governance, industrial development and improvement of people’s livelihood service capability.

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