Editorial Board Members’ Collection Series: Big Earth Data Science: Applications, Challenges and Future Trends

Dear Colleagues,

The increasing exploitation of natural resources, global change, and increasing human population make sustainability challenges more complex and dynamic than before. The digital transformation of our society provides new tools and methods to identify and understand the complexity of natural and social systems and phenomena. Big Data is the highlight of the new data era since it is such a revolutionary invention for exploring and understanding the world. Big data is at the forefront of the integration of geoscience, information science, and space science, as well as technology, and it is expected that Big Earth Data will provide new prospects for the development of Earth science. Big Earth Data science encompasses methodological and technological activities that support the systemic discovery of information from Big Earth Data. The key objective of Big Earth Data science is the scientific comprehension, modeling, and application of the processes, to generate information from the data and provide the knowledge required to address global sustainability challenges.

With the development of remote-sensing satellites and increasingly high-tech "in situ" instruments in recent years, Earth observation has become increasingly sophisticated. There are also increasing offerings of high-quality Earth observation data based on recent technical breakthroughs regarding monitoring, spatial-distributed modeling, data collection, storage, and distribution. The vast amounts of proximal and distal remote-sensing data that are available play an important role in tackling current and future key challenges, such as climate change, natural resources’ management, agriculture, environment, or disaster mitigation. However, the utilization, analysis, and interpretation of the ever-increasing amount of multisource data requires novel approaches and ideas.

This topic collection on ‘Big Earth Data Science: Applications, Challenges and Future Trends’ aims to collect the latest research and comprehensive reviews on big data science in Earth observation. The topics of interest may include but are not limited to the following:

• The latest and most advanced ideas regarding the new and efficient techniques for extracting information based on the new trends in advanced learning algorithms (including the newest ways that Big Earth Data can support and implement more sustainable development, preventing degradation of the natural environment and the depletion of natural resources.
• The latest techniques in high-performance computing applicable to the development and application of new image-processing techniques for an adequate and computationally efficient exploitation of remotely sensed scenes.
• New computationally efficient models for extracting information from huge remote-sensing datasets, with particular interest in the development of parallel and distributed techniques based on graphical processing units (GPUs) and grid/cloud-computing platforms.
• Recent advancements with a focus on addressing various environmental problems by means of innovative data collection, processing, and analytical solutions.
• Utilization of Big Earth Data on agricultural production and precision farming.
• New advances in monitoring systems and geospatial technologies such as drone technologies, hyperspectral satellite images, cube satellites, sensor networks, citizen science, cloud computing, etc.
• How Big Earth Data Science can better support decision-making processes addressing environmental policy needs.
• How to efficiently and effectively integrate heterogenous data and information sources.
• How to ensure the transparency and replicability of models and complex analytical workflows.

Dr. Gregory Giuliani
Prof. Dr. Shuguang Liu
Dr. Konstantinos X. Soulis
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• Big Earth Data
• remote sensing dataset
• cloud computing platforms
• data collection
• sustainable development
• environment
• natural resources
• environmental policies