常杪,冯雁,郭培坤,等.环境大数据概念、特征及在环境管理中的应用[J].中国环境管理,2015,7(6):26-30.
Chang Miao,Feng Yan,Guo Peikun,et al.Enviromental Big Data: Concept, Characteristics and Application in Enviromental Management[J].Chinese Journal of Environmental Management,2015,7(6):26-30. |
| 环境大数据概念、特征及在环境管理中的应用 |
| Enviromental Big Data: Concept, Characteristics and Application in Enviromental Management |
| DOI： |
| 中文关键词: 大数据 环境大数据 环境管理 应用场景 |
| 英文关键词:big data environmental big data environmental management application scenario |
| 基金项目:国家自然科学基金资助项目"基于大数据的城市环境质量改善管理调控决策系统研究"(71573149) |
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| 中文摘要: |
| 将大数据运用到环境管理领域是我国环境管理战略转型的重要举措.本文基于对大数据概念与特征分析,并结合环境领域的特点,阐述了环境大数据的概念、特征及在环境管理中所能发挥的作用.环境大数据即把大数据的核心理念和关键技术应用到环境领域,对海量环境数据进行采集、整合、存储、分析与应用等,具有数据规模大、种类多、处理速度快、价值密度低等特征.环境大数据的应用,对于政府、企业和公众都有重要意义.进一步对其在环境管理中的应用场景进行设想,发现其在环境规划编制、环境质量管理、污染源生命周期管理、环境应急以及公众参与等多方面都能发挥重要作用,以促使环境管理向数字化、网络化和精细化转变.最后针对环境大数据在数据处理、数据管理、数据应用现状方面存在的问题,提出了可能的解决思路. |
| 英文摘要: |
| The application of big data in environmental management is a key step towards China's strategy transitions in this fi eld. Combining the characteristics of environmental research and big data technology, this work elaborates the concepts, features and function of environmental big data in the fi eld of environmental management. Environmental big data makes full use of the core concepts and key technology of big data into environmental management and achieves the collection, integration, storage, analysis and application of mass environmental big data, with characteristics of large scale, great variety, rapid processing speed and low value density. There is no denying the fact that it will bring application prospect on the government, the industry and the public. Specifically, environmental big data plays an important role in the process ranging environmental planning, environmental quality management, life-cycle-based pollution source management, environmental emergency to public participation, thus promoting a digital, networking and meticulous transformation of environmental management. Lastly, the possible solutions to data processing, data management and data application status are put forward accordingly. |
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