Impacts of the data quality of remote sensing vegetation index on gross primary productivity estimation

Impacts of the data quality of remote sensing vegetation index on gross primary productivity estimation

ABSTRACTAs the most commonly used driven data for gross primary productivity (GPP) estimation, satellite remote sensing vegetation indexes (VI), such as the leaf area index (LAI), often seriously suffer from data quality problems induced by cloud contamination and noise. Although various filtering m...

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Bibliographic Details
Main Authors: Yinghao Sun, Dan Peng, Xiaobin Guan, Dong Chu, Yongming Ma, Huanfeng Shen
Format: Article
Language:English
Published: Taylor & Francis Group 2023-12-01
Series:GIScience & Remote Sensing
Subjects:
Filtering method
gross primary productivity
vegetation index
light use efficiency model
terrestrial ecosystem
Online Access:https://www.tandfonline.com/doi/10.1080/15481603.2023.2275421

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https://www.tandfonline.com/doi/10.1080/15481603.2023.2275421

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