Improving Imbalanced Land Cover Classification with K-Means SMOTE: Detecting and Oversampling Distinctive Minority Spectral Signatures

Improving Imbalanced Land Cover Classification with K-Means SMOTE: Detecting and Oversampling Distinctive Minority Spectral Signatures

Land cover maps are a critical tool to support informed policy development, planning, and resource management decisions. With significant upsides, the automatic production of Land Use/Land Cover maps has been a topic of interest for the remote sensing community for several years, but it is still fra...

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Bibliographic Details
Main Authors: Joao Fonseca, Georgios Douzas, Fernando Bacao
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Information
Subjects:
LULC classification
imbalanced learning
oversampling
data augmentation
clustering
Online Access:https://www.mdpi.com/2078-2489/12/7/266

Internet

https://www.mdpi.com/2078-2489/12/7/266

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