Improving land use/cover classification accuracy from random forest feature importance selection based on synergistic use of sentinel data and digital elevation model in agriculturally dominated landscape

HIGHLIGHTS

• who: Sau2019ad Ibrahim from the Department of Geography, Adamu Augie College of Education, Argungu PMB, Kebbi State, Nigeria have published the research: Improving Land Use/Cover Classification Accuracy from Random Forest Feature Importance Selection Based on Synergistic Use of Sentinel Data and Digital Elevation Model in Agriculturally Dominated Landscape, in the Journal: Agriculture 2023, 98 of 29/Dec/2022
• what: The aim of this study is to investigate how to improve the performance of LULC models to reduce prediction errors. This study shows the of the synergy between optical radar and elevation in improving the . . .
  

   

  

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