Big Earth Data science: an information framework for a sustainable planet

Abstract

The digital transformation of our society coupled with the increasing exploitation of natural resources makes sustainability challenges more complex and dynamic than ever before. These changes will unlikely stop or even decelerate in the near future. There is an urgent need for a new scientific approach and an advanced form of evidence-based decisionmaking towards the benefit of society, the economy, and the environment. To understand the impacts and interrelationships between humans as a society and natural Earth system processes, we propose a new engineering discipline, Big Earth Data science. This science is called to provide the methodologies and tools to generate knowledge from diverse, numerous, and complex data sources necessary to ensure a sustainable human society essential for the preservation of planet Earth. Big Earth Data science aims at utilizing data from Earth observation and social sensing and develop theories for understanding the mechanisms of how such a social-physical system operates and evolves. The manuscript introduces the universe of discourse characterizing this new science, its foundational paradigms and methodologies, and a possible technological framework to be implemented by applying an ecosystem approach. CASEarth and GEOSS are presented as examples of international implementation attempts. Conclusions discuss important challenges and collaboration opportunities. ARTICLE HISTORY

Supporting food systems transformation: The what, why, who, where and how of mission-oriented agricultural innovation systems

“…This can be combined with agricultural and food systems assessment and modelling approaches focusing for example on resilience ( Meuwissen et al, 2019 ; Tittonell, 2020 ), and drawing on recent frameworks to analyse different aspects of food systems transformation ( Gaitán-Cremaschi et al, 2019 ; Hebinck et al, 2018 ; Kanter et al, 2015 ; Termeer et al, 2018 ; Zurek et al, 2018 ). Such analysis may make use of data science or citizen science driven approaches bringing together large datasets of biophysical and socioeconomic data to track mission evolution ( Beza et al, 2017 ; Fielke et al, 2020 ; Guo et al, 2020 ; Klerkx et al, 2019 ; Sauermann et al, 2020 ). Since MAIS are often global with national or regional ‘branches’, initiatives like the Food Systems Dashboard ( Fanzo et al, 2020 ), the CGIAR Platform for Big Data in Agriculture, the Agricultural Science and Technology Indicators network (ASTI), and Capacity Development for Agricultural Innovation Systems project (CDAIS) could play roles in enabling or hosting ‘MAIS mapping’.…”

Global Action on SDGs: Policy Review and Outlook in a Post-Pandemic Era

“…Big Earth data science is worth developing to provide the methodologies and tools of generating knowledge from diverse, numerous, and complex data sources. Doing so is necessary and essential to ensuring a sustainable human society for the preservation of planet Earth [122,123], for example, evaluating clean water and sanitation and life below the water by using earth observation systems [124], and using population movement data to assess cities' health [125].…”

Modeling Conditions Appropriate for Wildfire in South East China – A Machine Learning Approach

“…This has led to the concept of big Earth data, which highlights the pooling of multidisciplinary concepts and resources to maximize the benefits of this growing technological potential for Earth systems science (Guo, 2017a,b). Big Earth data are simply big data for Earth systems science and make use of traditional fields such as mathematics, statistics, computer science, remote sensing, geographic information systems (GIS), and the emerging fields of machine learning, data mining, and artificial intelligence, however, scale variance and complexities of spatial temporal data add to the challenges of data processing unlike big data (Bondur, 2014;Guo et al, 2020).…”