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您的检索式：作者名="Stuart Minchin"
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| 1 | Digital earth Australia-unlocking new value from earth observation data显示文摘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. | Trevor Dhu Bex Dunn Ben Lewis Leo Lymburner Norman Mueller Erin Telfer Adam Lewis Alexis McIntyre Stuart Minchin Claire Phillips | 2017 | Big Earth Data2017，1，1： | 2 |
| 2 | Rapid,high-resolution detection of environmental change over continental scales from satellite data–the Earth Observation Data Cube显示文摘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. | Adam Lewis Leo Lymburner Matthew B.J.Purss Brendan Brooke Ben Evans Alex Ip Arnold G.Dekker James R.Irons Stuart Minchin Norman Mueller Simon Oliver Dale Roberts Barbara Ryan Medhavy Thankappan Rob Woodcock Lesley Wyborn | 2016 | International Journal of Digital Earth2016，9，1： | 0 |
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