大数据GIS
- 1 深圳大学空间信息智能感知与服务深圳市重点实验室,广东 深圳,518060;2 武汉大学测绘遥感信息工程国家重点实验室,湖北 武汉,430079
基金项目:
国家自然科学基金资助项目(41371377)；深圳市科技研发资金资助项目(ZDSY20121019111146499,JSGG20121026111056204)；深圳市战略性新兴产业发展专项资金资助项目(JCYJ20121019111128765)
作者简介:
李清泉,博士,教授。主要研究方向为时空数据挖掘、多传感器集成数据采集、精密工业及工程测量。
- 收稿日期:
2014-02-24
- 修回日期:
2014-06-05
- 刊出日期:
2014-06-05
摘要: 目的 大数据不仅使世界认识到数据的重要性,更引发了许多行业从根本上的变革。大数据时代也对GIS提出了诸多挑战,如海量、多源、异构数据的存储与管理以及面对大量噪音的价值挖掘等。作为空间数据管理、分析以及可视化的重要工具,为适应大数据的需求,GIS必须在大数据时代做出改变和调整。针对大数据的几个“V”特性分析了传统GIS所受到的挑战,在前期相关研究的基础上,从GIS空间数据管理、空间数据分析以及可视化三方面进一步阐述了大数据GIS应具有的特征。
Big Data GIS
- 1Shenzhen Key Laboratory of Spatial Smart Sensing and Services,Shenzhen University,Shenzhen 518060,China;2State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University,Wuhan 430079,China
Funds:
The National Natural Science Foundation of China,No.41371377;Shenzhen Scientific Research and DevelopmentFunding Program,Nos.ZDSY20121019111146499,JSGG20121026111056204;Shenzhen Dedicated Funding of Strategic Emerging In-dustry Development Program,No.JCYJ20121019111128765.
Author Bio:
LI Qingquan,PhD,professor,specializes in spatial-temporal data mining,multi-sensor integration,and industry and engi-neering surveying.
- Received Date:
2014-02-24
- Rev Recd Date:
2014-06-05
- Publish Date:
2014-06-05
Abstract: Objective Big data is changing the world,and also posing challenges for GIS.The volume,velocity,and variety of these data challenge the data management ability of GIS,while the veracity and value is-sues of big data challenge spatial analysis theory and methods.Thus,as a tool focusing on spatial datamanagement,analysis and visualization,GIS has to make necessary adjustments and changes to meetthe big data requirements.This paper discusses the challenges based on the 5Vproperties of big data,and then,analyzes three characteristics of future GIS in the big data era,which are:①scalable data management,②data-driven modeling and data mining,and③ geo-computational visual analytic.
李清泉, 李德仁. 大数据GIS[J]. 武汉大学学报 ● 信息科学版, 2014, 39(6): 641-644. doi: 10.13203/j.whugis20140150
LI Qingquan, LI Deren. Big Data GIS[J]. Geomatics and Information Science of Wuhan University, 2014, 39(6): 641-644. doi: 10.13203/j.whugis20140150
| Citation: |
LI Qingquan, LI Deren. Big Data GIS[J]. Geomatics and Information Science of Wuhan University, 2014, 39(6): 641-644. doi: 10.13203/j.whugis20140150
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