生态环境大数据面临的机遇与挑战

随着大数据时代的到来和大数据技术的迅猛发展,生态环境大数据的建设和应用已初露端倪。为了全面推进生态环境大数据的建设和应用,综述了生态环境大数据在解决生态环境问题中的机遇和优势,并分析了生态环境大数据在应用中所面临的挑战。总结和概括了大数据的概念与特征,又结合生态环境领域的特点,分析了生态环境大数据的特殊性和复杂性。重点阐述了生态环境大数据在减缓环境污染、生态退化和气候变化中的机遇,主要从数据存储、处理、分析、解释和展示等方面阐述生态环境大数据相较于传统数据的优势,通过这些优势说明生态环境大数据将有助于全面提高生态环境治理的综合决策水平。虽然生态环境大数据的应用前景广阔,但也面临着重重挑战,在数据共享和开放、应用创新、数据管理、技术创新和落地、专业人才培养和资金投入等方面还存在着许多问题和困难。在以上分析的基础上,提出了生态环境大数据未来的发展方向,包括各类生态环境数据的标准化、建设生态环境大数据存储与处理分析平台和推动国内外生态环境大数据平台的对接。

The opportunities and challenges presented by ecological environment big data

With the arrival of the era of big data and the rapid development of big data technology, the construction and application of ecological environment big data have been initiated. To comprehensively promote the construction and application of ecological environment big data, we summarize in the present paper the opportunities and advantages presented by ecological environment big data in terms of solving ecological environment problems, and analyze the challenges faced regarding the application of ecological environment big data. We review the concept and basic features of big data and present the particularity and complexity of the characteristics of ecological environment big data,taking into consideration the characteristics of the ecological environment. Subsequently, we primarily analyze the opportunities presented by ecological environment big data in mitigating environmental pollution, ecological degradation, and climate change from the aspects of data storage, data processing, data analysis, data interpretation, and presentation, and compare these with the use of traditional ecological environment data. The advantages of ecological environment big data indicate that this type of data can help us to improve the comprehensive decision-making level of ecological environment management. Although prospects for the applications of ecological environment big data in China are promising, there exist potential difficulties and challenges, such as data sharing, dataassessing, data application innovation, data management, technological innovation and launch, professional personnel training, and capital investment. Finally, we propose the following three priority areas concerning ecological environment big data based on our thorough review: (1) standardization of all types of ecological environment data; (2) building the storage, processing, and analysis platforms of ecological environment big data storage and processing analysis; (3) pushing forward the docking of ecological environment big data at home and abroad.