Trend features derived from dense landsat time series in an

HIGHLIGHTS

• who: Engine and collaborators from the Institute of Ecology, College of Urban and Environmental Sciences and Key Laboratory for Earth Surface School of Information Engineering, China University of Geosciences, Beijing, China have published the Article: Trend Features Derived from Dense Landsat Time Series in an, in the Journal: (JOURNAL) of 10/08/2021
• what: The RF classifier provided information on the pixel-level uncertainty in this study, which was calculated by 1-Pmax, with Pmax the maximum probability of being classified as each land cover class .
• how: In this study taking advantage of . . .
  

   

  

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