hakimabdi

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# title         : Machine learning exercise for Sentinel-2 data
# purpose       : Implementing a machine learning workflow in R 
# author        : Abdulhakim M. Abdi (Twitter: @HakimAbdi / www.hakimabdi.com)
# input         : A multi-temporal raster stack of Sentinel-2 data comprising scenes from four dates 
# output        : One classified land cover map from each of three machine learning algorithms  
# Note 1        : This brief tutorial assumes that you are already well-grounded in R concepts and are 
#               : familiar with image classification procedure and terminology
# Reference		  : Please cite Abdi (2020): "Land cover and land use classification performance of machine learning 
#				        : algorithms in a boreal landscape using Sentinel-2 data" in GIScience & Remote Sensing if you find this 

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