About this Research Topic
Whether it is atmosphere, water sources, or soil, the pollution of natural environment is always an issue that needs particular attention. Environmental pollution problems require long-term and high-precision monitoring. In recent years, the combination of spectral detection methods, imaging technologies, and artificial intelligence algorithms has provided a new approach for environmental monitoring and remote sensing. For different environmental samples, the systems used to obtain spectral information are also different. For remote sensing data, the target and the environment have a high similarity, and the research on data processing is also the focus of academic attention. Addressing hardware and software technologies in this field will contribute to the sustainable development of the Earth’s environment as well as the harmonious coexistence of man and nature in the future.
This Research Topic underlines how to communicate and discuss advanced methods to detect and identify potential environmental pollution. In the long-term large-scale monitoring, there are high requirements for the accuracy and efficiency of artificial intelligence methods. Effective monitoring and early warning give succor to determination of response methods as soon as possible and contribute to environmental sustainable development. Promoting the continued development of this field towards intelligence will be of great significance to both industry and the environment. The development of advanced spectroscopic techniques can objectively reflect the results of environmental monitoring in terms of physical and chemical aspects. The advancement of portable instruments and equipment can further develop more application scenarios and make monitoring more convenient. Efficient intelligent algorithms can facilitate monitoring faster, more accurately, and at lower cost.
This Research Topic welcomes high-quality Original Research and Review Articles related to the creation, collection, storage, processing, modelling, interpretation, display and dissemination of data and information for the Environmental Sciences. Particular focus will be given to the following topics, but not be limited to:
• Environmental monitoring (water, air, and soil quality monitoring)
• Remote sensing of the environment
• Spectroscopy (NIRS, LIBS, Raman, etc)
• Muitispectral/Hyperspectral imaging by dedicated and portable equipments
• Image analysis and processing
• Mathematical methods for inverse problems
• Decision support systems
• Data management and mining
• Artificial intelligence and big data
• Environmental statistics and machine learning
• Spectral fusion and information fusion
• Sensors, biosensors, and chemosensors
• Spatial information technologies
This Research Topic underlines how to communicate and discuss advanced methods to detect and identify potential environmental pollution. In the long-term large-scale monitoring, there are high requirements for the accuracy and efficiency of artificial intelligence methods. Effective monitoring and early warning give succor to determination of response methods as soon as possible and contribute to environmental sustainable development. Promoting the continued development of this field towards intelligence will be of great significance to both industry and the environment. The development of advanced spectroscopic techniques can objectively reflect the results of environmental monitoring in terms of physical and chemical aspects. The advancement of portable instruments and equipment can further develop more application scenarios and make monitoring more convenient. Efficient intelligent algorithms can facilitate monitoring faster, more accurately, and at lower cost.
This Research Topic welcomes high-quality Original Research and Review Articles related to the creation, collection, storage, processing, modelling, interpretation, display and dissemination of data and information for the Environmental Sciences. Particular focus will be given to the following topics, but not be limited to:
• Environmental monitoring (water, air, and soil quality monitoring)
• Remote sensing of the environment
• Spectroscopy (NIRS, LIBS, Raman, etc)
• Muitispectral/Hyperspectral imaging by dedicated and portable equipments
• Image analysis and processing
• Mathematical methods for inverse problems
• Decision support systems
• Data management and mining
• Artificial intelligence and big data
• Environmental statistics and machine learning
• Spectral fusion and information fusion
• Sensors, biosensors, and chemosensors
• Spatial information technologies
Keywords: environmental monitoring, spectral detection, atmospheric environment, water quality, machine and deep learning, artificial intelligence
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
