Classification of rice heavy metal stress levels based on phenological characteristics using remote sensing time-series images and data mining algorithms

HIGHLIGHTS

• who: Tianjiao Liu et al. from the School of Information Engineering, China University of Geosciences, Beijing, China have published the article: Classification of Rice Heavy Metal Stress Levels Based on Phenological Characteristics Using Remote Sensing Time-Series Images and Data Mining Algorithms, in the Journal: (JOURNAL) of 17/09/2013
• what: This study aims to develop a method for accurately evaluating heavy metal stress in rice based on phenology. Images with cloud cover of less than 30% in the research area were used as inputs of the ESTARFM algorithm, and a series of fusion images . . .
  

   

  

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