Data cubes uncover spatiotemporal dynamics in the Earth system
Today, an unprecedented availability of data streams is describing different facets of the Earth system. Many initiatives within and beyond the Earth system sciences are exploring new approaches to overcome the barrier of joint interpretation via so-called “Data Cubes“. Here, we introduce the concept of Earth system data cubes and how to operate on them. Several case studies will be shown how we can exploit these data to understand complex spatiotemporal patterns in land-surface processes such as extreme events and global trends.
Miguel D. Mahecha leads the research group on “Earth System Data Science” at the Remote Sensing Centre for Earth System Research, Leipzig University, Germany. His scholarly interests generally revolve around empowering Earth system sciences with data-driven methods. Examples are i) understanding the effect of climate extremes on the biosphere, ii) land-atmosphere interactions, and iii) biodiversity dynamics and climate change.