As an important information carrier, data records all kinds of real and network social activities. Cheaper and more convenient tools for storing, analyzing, sharing, and distributing data have led to an explosion in the volume of data around the world. Governments around the world and companies in various industries are realizing the tremendous value of big data in environmental governance. They use a variety of emerging big data analysis and processing tools to mine information from a large amount of unstructured data, form useful and valuable knowledge, and provide decision support for environmental governance methods and paths. In addition, artificial intelligence technologies, such as computer vision, machine learning, robotics, biometrics, image recognition, and natural language processing, have been widely used in various environmental protection fields. Through comprehensive and in-depth monitoring of environmental information, transmission and aggregation of environmental data and intelligent environmental management application scenarios, the level of intelligent decision-making and processing of the ecological environment has been comprehensively improved. These advances allow us to observe how environmental issues operate from big data and artificial intelligence to help policymakers modernize environmental governance. Therefore, how to better promote environmental governance through big data and artificial intelligence has become the focus of current academic research and management practice.
As a crucial field of social governance, the modernization of the environmental governance system and governance capacity is an important aspect. Environmental governance provides a great space for the application of big data and artificial intelligence because of the complex space-time scale, the complex interaction between pollutants and pollution media, and the ambiguity and uncertainty of stakeholder decisions. The systematic understanding and revelation of the role and mechanism of big data and artificial intelligence in the mode transformation and means innovation of environmental governance is in line with the needs of global sustainable development strategy, and has a positive significance in the collaborative solution of environmental problems across disciplines.
This Research Topic aims to collect Original Research and Review articles that are relevant to theoretical frameworks, research methods, case studies, empirical studies, or econometric models of big data and artificial intelligence in promoting environmental governance. Environmental issues of interest include air pollution prevention and control, soil environment comprehensive control, forest ecological restoration and wetland protection, desertification prevention and control, soil erosion prevention and control, illegal land use, illegal construction, urban and rural environment comprehensive control, urban inland river (lake) water pollution control and resource allocation across regions.
We welcome contributions that provide theoretical and/or practical implications from the following topic directions based on big data and artificial intelligence perspectives.
• Environmental monitoring and governance measures based on big data
• Public policy on environmental governance
• Influencing factors of environmental governance
• Technical path to governance environment with big data
• Performance evaluation
• Organizational change in environmental governance
• Human resource management of environmental governance
• Application of artificial intelligence and other new technologies in environmental governance
• Internal mechanism of big data promoting environmental governance
• Process, path, and means promoting environmental governance
• Typical case analysis
• The social network of environmental governance
• Collaborative governance across regions
As an important information carrier, data records all kinds of real and network social activities. Cheaper and more convenient tools for storing, analyzing, sharing, and distributing data have led to an explosion in the volume of data around the world. Governments around the world and companies in various industries are realizing the tremendous value of big data in environmental governance. They use a variety of emerging big data analysis and processing tools to mine information from a large amount of unstructured data, form useful and valuable knowledge, and provide decision support for environmental governance methods and paths. In addition, artificial intelligence technologies, such as computer vision, machine learning, robotics, biometrics, image recognition, and natural language processing, have been widely used in various environmental protection fields. Through comprehensive and in-depth monitoring of environmental information, transmission and aggregation of environmental data and intelligent environmental management application scenarios, the level of intelligent decision-making and processing of the ecological environment has been comprehensively improved. These advances allow us to observe how environmental issues operate from big data and artificial intelligence to help policymakers modernize environmental governance. Therefore, how to better promote environmental governance through big data and artificial intelligence has become the focus of current academic research and management practice.
As a crucial field of social governance, the modernization of the environmental governance system and governance capacity is an important aspect. Environmental governance provides a great space for the application of big data and artificial intelligence because of the complex space-time scale, the complex interaction between pollutants and pollution media, and the ambiguity and uncertainty of stakeholder decisions. The systematic understanding and revelation of the role and mechanism of big data and artificial intelligence in the mode transformation and means innovation of environmental governance is in line with the needs of global sustainable development strategy, and has a positive significance in the collaborative solution of environmental problems across disciplines.
This Research Topic aims to collect Original Research and Review articles that are relevant to theoretical frameworks, research methods, case studies, empirical studies, or econometric models of big data and artificial intelligence in promoting environmental governance. Environmental issues of interest include air pollution prevention and control, soil environment comprehensive control, forest ecological restoration and wetland protection, desertification prevention and control, soil erosion prevention and control, illegal land use, illegal construction, urban and rural environment comprehensive control, urban inland river (lake) water pollution control and resource allocation across regions.
We welcome contributions that provide theoretical and/or practical implications from the following topic directions based on big data and artificial intelligence perspectives.
• Environmental monitoring and governance measures based on big data
• Public policy on environmental governance
• Influencing factors of environmental governance
• Technical path to governance environment with big data
• Performance evaluation
• Organizational change in environmental governance
• Human resource management of environmental governance
• Application of artificial intelligence and other new technologies in environmental governance
• Internal mechanism of big data promoting environmental governance
• Process, path, and means promoting environmental governance
• Typical case analysis
• The social network of environmental governance
• Collaborative governance across regions
