Adaptive Decomposition and Multitimescale Analysis of Long Time Series of Climatic Factors and Vegetation Index Based on ICEEMDAN-SVM

Adaptive Decomposition and Multitimescale Analysis of Long Time Series of Climatic Factors and Vegetation Index Based on ICEEMDAN-SVM

Climate change is of great significance to vegetation coverage. However, the long time series of climatic factors and vegetation index are nonstationary and nonlinear, containing different information in frequency and time scales. The study innovatively integrated a support vector machine (SVM) and...

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Bibliographic Details
Main Authors: Qianqian Sun, Chao Liu, Tianyang Chen, Anbing Zhang, Chunyang Liu, Yuan Tao
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Climate change
improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN)
Loess Plateau (LP)
multiple timescales
normalized difference vegetation index (NDVI)
support vector machine(SVM)
Online Access:https://ieeexplore.ieee.org/document/9844789/

Internet

https://ieeexplore.ieee.org/document/9844789/

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