Gap Filling for Historical Landsat NDVI Time Series by Integrating Climate Data

Gap Filling for Historical Landsat NDVI Time Series by Integrating Climate Data

High-quality Normalized Difference Vegetation Index (NDVI) time series are essential in studying vegetation phenology, dynamic monitoring, and global change. Gap filling is the most important issue in reconstructing NDVI time series from satellites with high spatial resolution, e.g., the Landsat ser...

Full description

Bibliographic Details
Main Authors: Wentao Yu, Jing Li, Qinhuo Liu, Jing Zhao, Yadong Dong, Xinran Zhu, Shangrong Lin, Hu Zhang, Zhaoxing Zhang
Format: Article
Language:English
Published: MDPI AG 2021-01-01
Series:Remote Sensing
Subjects:
gap filling
time series reconstruction
NDVI time series
vegetation growth
climate data
radial basis function networks (RBFN)
Online Access:https://www.mdpi.com/2072-4292/13/3/484

Internet

https://www.mdpi.com/2072-4292/13/3/484

Similar Items