Classification of Rice Heavy Metal Stress Levels Based on Phenological Characteristics Using Remote Sensing Time-Series Images and Data Mining Algorithms

Classification of Rice Heavy Metal Stress Levels Based on Phenological Characteristics Using Remote Sensing Time-Series Images and Data Mining Algorithms

Heavy metal pollution in crops leads to phenological changes, which can be monitored by remote sensing technology. The present study aims to develop a method for accurately evaluating heavy metal stress in rice based on remote sensing phenology. First, the enhanced spatial and temporal adaptive refl...

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Bibliographic Details
Main Authors: Tianjiao Liu, Xiangnan Liu, Meiling Liu, Ling Wu
Format: Article
Language:English
Published: MDPI AG 2018-12-01
Series:Sensors
Subjects:
heavy metal stress
time-series
remote sensing phenology
MODIS and Landsat
ensemble model
feature selection
Online Access:https://www.mdpi.com/1424-8220/18/12/4425

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