Think global,cube local:an Earth Observation Data Cube’s contribution to the Digital Earth vision

The technological landscape for managing big Earth observation(EO)data ranges from global solutions on large cloud infrastructures with web-based access to self-hosted implementations.EO data cubes are a leading technology for facilitating big EO data analysis and can be deployed on different spatial scales:local,national,regional,or global.Several EO data cubes with a geographic focus(“local EO data cubes”)have been implemented.However,their alignment with the Digital Earth(DE)vision and the benefits and trade-offs in creating and maintaining them ought to be further examined.We investigate local EO data cubes from five perspectives(science,business and industry,government and policy,education,communities and citizens)and illustrate four examples covering three continents at different geographic scales(Swiss Data Cube,semantic EO data cube for Austria,DE Africa,Virginia Data Cube).A local EO data cube can benefit many stakeholders and players but requires several technical developments.These developments include enabling local EO data cubes based on public,global,and cloud-native EO data streaming and interoperability between local EO data cubes.We argue that blurring the dichotomy between global and local aligns with the DE vision to access the world’s knowledge and explore information about the planet.

Digital earth Australia-unlocking new value from earth observation data

Petascale archives of Earth observations from space(EOS)have the potential to characterise water resources at continental scales.For this data to be useful,it needs to be organised,converted from individual scenes as acquired by multiple sensors,converted into“analysis ready data”,and made available through high performance computing platforms.Moreover,converting this data into insights requires integration of non-EOS data-sets that can provide biophysical and climatic context for EOS.Digital Earth Australia has demonstrated its ability to link EOS to rainfall and stream gauge data to provide insight into surface water dynamics during the hydrological extremes of flood and drought.This information is supporting the characterisation of groundwater resources across Australia’s north and could potentially be used to gain an understanding of the vulnerability of transport infrastructure to floods in remote,sparsely gauged regions of northern and central Australia.

Rapid,high-resolution detection of environmental change over continental scales from satellite data–the Earth Observation Data Cube

The effort and cost required to convert satellite Earth Observation(EO)data into meaningful geophysical variables has prevented the systematic analysis of all available observations.To overcome these problems,we utilise an integrated High Performance Computing and Data environment to rapidly process,restructure and analyse the Australian Landsat data archive.In this approach,the EO data are assigned to a common grid framework that spans the full geospatial and temporal extent of the observations–the EO Data Cube.This approach is pixel-based and incorporates geometric and spectral calibration and quality assurance of each Earth surface reflectance measurement.We demonstrate the utility of the approach with rapid time-series mapping of surface water across the entire Australian continent using 27 years of continuous,25 m resolution observations.Our preliminary analysis of the Landsat archive shows how the EO Data Cube can effectively liberate high-resolution EO data from their complex sensor-specific data structures and revolutionise our ability to measure environmental change.