The Australian Geoscience Data Cube - foundations and lessons learned

By A. Lewis, Simon Oliver, Leo Lymburner, B. Evans, L. Wyborn, N. Mueller, Gregory Raevksi, J. Hooke, R. Woodcock, J. Sixsmith and 19 more. 2017

298 citations recorded by the source corpus.

Abstract The Australian Geoscience Data Cube (AGDC) aims to realise the full potential of Earth observation data holdings by addressing the Big Data challenges of volume, velocity, and variety that otherwise limit the usefulness of Earth observation data. There have been several iterations and AGDC version 2 is a major advance on previous work. The foundations and core components of the AGDC are: (1) data preparation, including geometric and radiometric corrections to Earth observation data to produce standardised surface reflectance measurements that support time-series analysis, and collection management systems which track the provenance of each Data Cube product and formalise re-processing decisions; (2) the software environment used to manage and interact with the data; and (3) the supporting high performance computing environment provided by the Australian National Computational Infrastructure (NCI). A growing number of examples demonstrate that our data cube approach allows analysts to extract rich new information from Earth observation time series, including through new methods that draw on the full spatial and temporal coverage of the Earth observation archives. To enable easy-uptake of the AGDC, and to facilitate future cooperative development, our code is developed under an open-source, Apache License, Version 2.0. This open-source approach is enabling other organisations, including the Committee on Earth Observing Satellites (CEOS), to explore the use of similar data cubes in developing countries.

Subfields: Artificial Intelligence, Geochemistry and Petrology, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/58cee7ff836083beee18d28aafcb061588392a57

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Zhe Zhu
2. Thomas R. Loveland
3. Curtis E. Woodcock
4. Warren B. Cohen
5. M. Wulder
6. David P. Roy
7. Joanne C. White
8. Patrick Hostert

In Geochemistry and Petrology

1. Warren B. Cohen

In Global and Planetary Change

1. Zhe Zhu
2. Curtis E. Woodcock
3. David P. Roy
4. Thomas R. Loveland
5. M. Wulder
6. Joanne C. White
7. Warren B. Cohen
8. Robert E. Kennedy

Citations in the corpus

• Current status of Landsat program, science, and applications (2019, background): “Additional corrections for satellite view angle and terrain illumination effects can also be implemented (Lewis et al., 2017; Roy et al., 2016a).”
• Analysis Ready Data: Enabling Analysis of the Landsat Archive (2018, unknown): “, seasonal to multidecadal) analyses [3-6].”
• Land cover 2.0 (2018, background): “…to the data ’ , many government agencies are building high performance computing systems that host large satellite data collections, such as the NASA Earth Exchange (NEX) (Nemani et al. 2011) and the Australian Geoscience Data Cube (AGDC) (Lewis et al. 2017), to enable large volume processing.”