The Australian Geoscience Data Cube - Foundations and lessons learned

REMOTE SENSING OF ENVIRONMENT

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Article

Lewis, Adam¹  Oliver, Simon¹  Evans, Ben²  Wyborn, Lesley²  Mueller, Norman¹  Raevksi, Gregory¹  Hooke, Jeremy¹  Woodcock, Rob³  Sixsmith, Joshua¹  Wu, Wenjun¹  Tan, Peter¹  Li, Fuqin¹  Killough, Brian⁴  Minchin, Stuart¹  Roberts, Dale^1,2  Ayers, Damien¹  Bala, Biswajit¹  Dwyer, John⁵  Dekker, Arnold³  Dhu, Trevor¹  Hicks, Andrew¹  Ip, Alex¹  Purss, Matt¹  Richards, Clare²  Sagar, Stephen¹  Trenham, Claire²  Wang, Peter³  Wang, Lan-Wei¹ 

[1] Geosci Australia, GPO Box 378, Canberra, ACT 2601, Australia

[2] Australian Natl Univ, Canberra, ACT 2601, Australia

[3] CSIRO, GPO Box 1700, Canberra, ACT 2600, Australia

[4] NASA, Langley Res Ctr, 1 Nasa Dr, Hampton, VA 23666 USA

[5] US Geol Survey, Earth Resources Observat & Sci EROS Ctr, 47914 252nd St, Sioux Falls, SD 57198 USA

关键词: Landsat;    Time-series;    Big data;    Data cube;    High performance computing;    High performance data;    Collection management;    Geometric correction;    Pixel quality;    Australian Geoscience Data Cube;   

DOI  :  10.1016/j.rse.2017.03.015

来源: Elsevier

【 摘 要 】

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. Crown Copyright (C) 2017 Published by Elsevier Inc.

【 授权许可】

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