You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Correlation between NDWI and tide height works well for identifying intertidal candidate pixels. However, it can produce noisy and unpredictable results when our data is noisy or sparse through time.
Significance (e.g. p-value) of the relationship between NDWI and tide height could be a more robust alternative to correlation. This is supported by the lag_linregress_3D function in DEA Tools, so could be a trivial change.
The text was updated successfully, but these errors were encountered:
Correlation between NDWI and tide height works well for identifying intertidal candidate pixels. However, it can produce noisy and unpredictable results when our data is noisy or sparse through time.
Significance (e.g. p-value) of the relationship between NDWI and tide height could be a more robust alternative to correlation. This is supported by the
lag_linregress_3D
function in DEA Tools, so could be a trivial change.The text was updated successfully, but these errors were encountered: