Evaluations and comparisons of rule-based and machine-learning-based methods to retrieve satellite-based vegetation phenology using MODIS and USA National Phenology Network data

Evaluations and comparisons of rule-based and machine-learning-based methods to retrieve satellite-based vegetation phenology using MODIS and USA National Phenology Network data

Vegetation phenology is a sensitive indicator that reflects the vegetation–atmosphere interactions and vegetation processes under global atmospheric changes. Fast-developing remote sensing technologies that monitor the land surface at high spatial and temporal resolutions have been widely used in ve...

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Bibliographic Details
Main Authors: Qinchuan Xin, Jing Li, Ziming Li, Yaoming Li, Xuewen Zhou
Format: Article
Language:English
Published: Elsevier 2020-12-01
Series:International Journal of Applied Earth Observations and Geoinformation
Subjects:
Phenology
Ground observation
Remote sensing
Time series analysis
Machine learning
Online Access:http://www.sciencedirect.com/science/article/pii/S0303243420300209

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http://www.sciencedirect.com/science/article/pii/S0303243420300209

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