Article(id=1242136678068990633, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1242136669516804758, articleNumber=null, orderNo=7, doi=10.3981/j.issn.1000-7857.2018.03.005, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1511971200000, receivedDateStr=2017-11-30, revisedDate=1515254400000, revisedDateStr=2018-01-07, acceptedDate=null, acceptedDateStr=null, onlineDate=1519894753640, onlineDateStr=2018-03-01, pubDate=1518451200000, pubDateStr=2018-02-13, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1519894753640, onlineIssueDateStr=2018-03-01, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774078061831, creator=sys-migrate, updateTime=1774078061831, updator=sys-migrate, issue=Issue{id=1242136669516804758, tenantId=1146029695717560320, journalId=1146031591421210625, year='2018', volume='36', issue='3', pageStart='1', pageEnd='124', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=3, issueType=-1, specialIssue=null, createTime=1774078059792, creator=sys-migrate, updateTime=1774078059792, updator=sys-migrate, preIssue=null, nextIssue=null, ext=null, issueFiles=null}, startPage=41, endPage=48, ext={EN=ArticleExt(id=1242136680531043026, articleId=1242136678068990633, tenantId=1146029695717560320, journalId=1146031591421210625, language=EN, title=Research on the geo-environment in the era of big data, columnId=1242116903087440448, journalTitle=Science & Technology Review, columnName=Spescial Issues, runingTitle=null, highlight=null, articleAbstract=The study of geographical environment characteristics and evolution rules is an important scientific support for recognizing the international geopolitical situation and safeguarding national security. Since 21 century, the rise of frequency and influence of all kinds of geopolitical events causes a serious threat to China's geopolitical safety and implementation of "the Belt and Road Initiative". The occurrence of geopolitical events is the result of interaction of various geo-environmental factors. The analysis of the evolution process of multi-dimensional geopolitical elements is an important basis for simulation and early warning of geo-risk. This paper reviews the origin and historical progress of the research on geo-environment both at home and abroad, systematically combs the main observation means of geo-environmental factors, and sums up application results of big data technology in the field of geo-environment research. Research shows that single geopolitical events have a high degree randomness, but the occurrence of massive events is affected by various geo-environment factors. Based on geo-environment system theory, the paper describes the complex relationship between geographical environment factors by using a large data analysis method, which helps to solve the problem of specific geographical. Finally, the paper suggests that the future geo-environment research should be guided by the geo-environment system theory and uses big data mining and machine learning technology to construct a spatiotemporal simulation and intelligent analysis model of geo-environment., correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=qy3XjM2iEP/5kNzydCIO1g==, pdfFileSize=832431, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=1. Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;
2. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China, fund=null, authors=JIANG Dong^1,2, WANG Qian^1,2, DING Fangyu^1,2, authorsList=JIANG Dong, WANG Qian, DING Fangyu), CN=ArticleExt(id=1242136679687987909, articleId=1242136678068990633, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=大数据时代的地缘环境研究, columnId=1242116902361830275, journalTitle=科技导报, columnName=专题论文, runingTitle=null, highlight=null, articleAbstract=地缘环境特征和演变规律的研究是认知国际地缘政治态势、保障国家安全的重要科学支撑。21世纪以来，各类地缘事件的发生频次和影响程度不断上升，严重威胁了中国地缘环境安全和“一带一路”倡议的实施。地缘事件的发生是多种地缘环境要素相互作用、相互影响的结果，分析多维度地缘要素的演变过程，是地缘风险模拟与预警的重要依据。本文回顾了国内外地缘环境研究的起源和历史进展，梳理了地缘环境要素的主要观测手段，归纳了大数据技术在地缘环境研究领域的应用成果。研究表明，单个地缘事件具有高度随机性，但海量事件的发生受各类地缘环境要素的影响和制约，基于地缘环境系统理论，利用大数据分析方法，可以发现地缘环境要素之间的复杂关系，有助于解决特定的地缘问题。未来的地缘环境研究应以地缘环境系统理论为指导，采用大数据信息挖掘和机器学习技术，构建地缘环境时空模拟与智能分析模式。, correspAuthors=null, authorNote=江东,研究员,研究方向为地缘环境模拟,电子信箱:jiangd@igsnrr.ac.cn, correspAuthorsNote=丁方宇(通信作者),博士研究生,研究方向为资源环境遥感应用,电子信箱:dingfy.17b@igsnrr.ac.cn, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=bK/1C9QFyNnRx04hgg1tEw==, pdfFileSize=832431, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=1. 中国科学院地理科学与资源研究所, 北京 100101;
2. 中国科学院大学资源与环境学院, 北京 100049, fund=中国科学院重点部署课题（ZDRW-ZS-2016-6-1）, authors=江东^1,2, 王倩^1,2, 丁方宇^1,2, authorsList=江东, 王倩, 丁方宇)}, authors=[Author(id=1277039922427065122, tenantId=1146029695717560320, journalId=null, articleId=1242136678068990633, orderNo=null, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=null, email=null, emailSecond=null, emailThird=null, correspondingAuthor=null, authorType=null, ext={EN=AuthorExt(id=null, tenantId=null, journalId=1146031591421210625, articleId=1242136678068990633, authorId=1277039922427065122, language=EN, stringName=JIANG Dong, WANG Qian, DING Fangyu, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=null, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=null, tenantId=null, journalId=1146031591421210625, 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