High-quality vegetation index product generation: A review of NDVI time series reconstruction techniques-Reference-Cited by-同舟云学术

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High-quality vegetation index product generation: A review of NDVI time series reconstruction techniques

Published:2021-12 Issue: Volume:105 Page:102640
ISSN:0303-2434
Container-title:International Journal of Applied Earth Observation and Geoinformation
language:en
Short-container-title:International Journal of Applied Earth Observation and Geoinformation

Author:

Li Shuang,Xu Liang,Jing Yinghong,Yin Hang,Li Xinghua,Guan Xiaobin

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Computers in Earth Sciences,Earth-Surface Processes,Global and Planetary Change

Reference138 articles.

1. Application of long short-term memory neural network model for the reconstruction of MODIS land surface temperature images;Arslan;J. Atmos. Sol.-Terr. Phys.,2019

2. Inter-comparison of four models for smoothing satellite sensor time-series data to estimate vegetation phenology;Atkinson;Remote Sens. Environ.,2012

3. A time series for monitoring vegetation activity and phenology at 10-daily time steps covering large parts of South America;Atzberger;Int. J. Digit. Earth,2011

4. TSAVI: a vegetation index which minimizes soil brightness effects on LAI and APAR estimation;Baret,1989

5. Multivariate interpolation to incorporate thematic surface data using inverse distance weighting (IDW);Bartier;Comput. Geosci.,1996

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