UNVI-Based Time Series for Vegetation Discrimination Using Separability Analysis and Random Forest Classification

UNVI-Based Time Series for Vegetation Discrimination Using Separability Analysis and Random Forest Classification

Land cover data is crucial for earth system modelling, natural resources management, and conservation planning. Remotely sensed time-series data capture dynamic behavior of vegetation, and have been widely used for land cover mapping. Temporal profiles of vegetation index (VI), especially normalized...

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Bibliographic Details
Main Authors: Hualiang Liu, Feizhou Zhang, Lifu Zhang, Yukun Lin, Siheng Wang, Yefeng Xie
Format: Article
Language:English
Published: MDPI AG 2020-02-01
Series:Remote Sensing
Subjects:
land cover
unvi
time series
phenology
jm distance
random forest
Online Access:https://www.mdpi.com/2072-4292/12/3/529

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