{"id":830209,"date":"2022-03-28T08:20:08","date_gmt":"2022-03-28T15:20:08","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=830209"},"modified":"2022-03-28T08:20:08","modified_gmt":"2022-03-28T15:20:08","slug":"digital-earth-australia-unlocking-new-value-from-earth-observation-data","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/digital-earth-australia-unlocking-new-value-from-earth-observation-data\/","title":{"rendered":"Digital earth Australia \u2013 unlocking new value from earth observation data"},"content":{"rendered":"

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 \u201canalysis ready data\u201d, 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\u2019s 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.<\/p>\n","protected":false},"excerpt":{"rendered":"

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 \u201canalysis ready data\u201d, and made available through high performance computing platforms. Moreover, converting this data 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