[Applications of eco-environmental big data: Progress and prospect].

Journal: Ying yong sheng tai xue bao = The journal of applied ecology
Published Date:

Abstract

With the advance of internet and wireless communication technology, the fields of ecology and environment have entered a new digital era with the amount of data growing explosively and big data technologies attracting more and more attention. The eco-environmental big data is based airborne and space-/land-based observations of ecological and environmental factors and its ultimate goal is to integrate multi-source and multi-scale data for information mining by taking advantages of cloud computation, artificial intelligence, and modeling technologies. In comparison with other fields, the eco-environmental big data has its own characteristics, such as diverse data formats and sources, data collected with various protocols and standards, and serving different clients and organizations with special requirements. Big data technology has been applied worldwide in ecological and environmental fields including global climate prediction, ecological network observation and modeling, and regional air pollution control. The development of eco-environmental big data in China is facing many problems, such as data sharing issues, outdated monitoring facilities and techno-logies, and insufficient data mining capacity. Despite all this, big data technology is critical to solving eco-environmental problems, improving prediction and warning accuracy on eco-environmental catastrophes, and boosting scientific research in the field in China. We expected that the eco-environmental big data would contribute significantly to policy making and environmental services and management, and thus the sustainable development and eco-civilization construction in China in the coming decades.

Authors

  • Miao Miao Zhao
    Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
  • Shi Cheng Zhao
    Xinyang Agricultural and Forestry University, Xinyang 464000, Henan, China.
  • Li Yun Zhang
    Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
  • Fen Zhao
    Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
  • Rui Shao
    Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
  • Li Xiang Liu
    Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
  • Hai Feng Zhao
    Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
  • Ming Xu
    Shenyang Analytical Application Center, Shimadzu (China) Co. Ltd., Shenyang, 167 Qingnian Street, Shenyang, 110016, PR China.