Linked remote sensing and Long Short-Term Memory (LSTM) models reveal how surface water storage dynamics influence river discharge
Description
Linked remote sensing and Long Short-Term Memory (LSTM) models reveal how surface water storage dynamics influence river discharge. This dataset is not publicly accessible because: It belongs to external collaborators. It can be accessed through the following means: The DOI for the final data release will be: (https://doi.org/10.5066/P14WYWSY). Format: The data will be housed at USGS's sciencebase.gov with an FGDC metadata .xml file as well as a csv file have been included along with model results for both remote sensing at the SWAT model subbasins. A link should be included on ScienceHub that will direct users to USGS's sciencebase. The DOI for the final data release will be: (https://doi.org/10.5066/P14WYWSY)
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Tags
- sentinel-time-series
- lstm-machine-learning
- remote-sensing
- surface-water-storage