Land Cover Mapping Using Sentinel-1 Time-Series Data and Machine-Learning Classifiers in Agricultural Sub-Saharan Landscape

Land Cover Mapping Using Sentinel-1 Time-Series Data and Machine-Learning Classifiers in Agricultural Sub-Saharan Landscape

This paper shows the efficiency of machine learning for improving land use/cover classification from synthetic aperture radar (SAR) satellite imagery as a tool that can be used in some sub-Saharan countries that experience frequent clouds. Indeed, we aimed to map the land use and land cover, especia...

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Bibliographic Details
Main Authors: Sara Dahhani, Mohamed Raji, Mustapha Hakdaoui, Rachid Lhissou
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Remote Sensing
Subjects:
SAR data
PCA
K-D tree KNN
time series
land use
random forest
Online Access:https://www.mdpi.com/2072-4292/15/1/65

Internet

https://www.mdpi.com/2072-4292/15/1/65

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