A methodology to reconstruct LAI time series data based on generative adversarial network and improved Savitzky-Golay filter

A methodology to reconstruct LAI time series data based on generative adversarial network and improved Savitzky-Golay filter

High-quality leaf area index (LAI) data is essential for regional and global ecology, climate and environment research. However, there are still many quality problems in the continuity of current LAI time series products. Here we developed a new comprehensive three-step reconstruction method (GANSG)...

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Bibliographic Details
Main Authors: Anqi Huang, Runping Shen, Wenli Di, Huimin Han
Format: Article
Language:English
Published: Elsevier 2021-12-01
Series:International Journal of Applied Earth Observations and Geoinformation
Subjects:
Remote sensing
Leaf area index
Time series
Data reconstruction
Generative adversarial network
Online Access:http://www.sciencedirect.com/science/article/pii/S0303243421003408

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