Related references
Note: Only part of the references are listed.Remote sensing estimation of phytoplankton absorption associated with size classes in coastal waters
Yu Huan et al.
ECOLOGICAL INDICATORS (2021)
A review of vegetation phenological metrics extraction using time-series, multispectral satellite data
Linglin Zeng et al.
REMOTE SENSING OF ENVIRONMENT (2020)
Incorporating environmental data in abundance-based algorithms for deriving phytoplankton size classes in the Atlantic Ocean
Timothy S. Moore et al.
REMOTE SENSING OF ENVIRONMENT (2020)
Spatially and temporally complete Landsat reflectance time series modelling: The fill-and-fit approach
Lin Yan et al.
REMOTE SENSING OF ENVIRONMENT (2020)
Contrasting chlorophyll-a seasonal patterns between nearshore and offshore waters in the Bohai and Yellow Seas, China: A new analysis using improved satellite data
Yueqi Wang et al.
CONTINENTAL SHELF RESEARCH (2020)
Multivariate DINEOF Reconstruction for Creating Long-Term Cloud-Free Chlorophyll-a Data Records From SeaWiFS and MODIS: A Case Study in Bohai and Yellow Seas, China
Yueqi Wang et al.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2019)
Extension of the growing season of phytoplankton in the western Baltic Sea in response to climate change
Norbert Wasmund et al.
MARINE ECOLOGY PROGRESS SERIES (2019)
Spatio-Temporal Reconstruction of MODIS NDVI by Regional Land Surface Phenology and Harmonic Analysis of Time-Series
Suman Kumar Padhee et al.
GISCIENCE & REMOTE SENSING (2019)
Weighted Double-Logistic Function Fitting Method for Reconstructing the High-Quality Sentinel-2 NDVI Time Series Data Set
Yingpin Yang et al.
REMOTE SENSING (2019)
Gap Filling of Missing Data for VIIRS Global Ocean Color Products Using the DINEOF Method
Xiaoming Liu et al.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2018)
A Method for Robust Estimation of Vegetation Seasonality from Landsat and Sentinel-2 Time Series Data
Per Jonsson et al.
REMOTE SENSING (2018)
Application of a generalized additive model (GAM) for estimating chlorophyll-a concentration from MODIS data in the Bohai and Yellow Seas, China
Yueqi Wang et al.
INTERNATIONAL JOURNAL OF REMOTE SENSING (2017)
Global evaluation of gap-filling approaches for seasonal NDVI with considering vegetation growth trajectory, protection of key point, noise resistance and curve stability
Ronggao Liu et al.
REMOTE SENSING OF ENVIRONMENT (2017)
Estimating sea surface salinity in the northern Gulf of Mexico from satellite ocean color measurements
Shuangling Chen et al.
REMOTE SENSING OF ENVIRONMENT (2017)
Performance of Smoothing Methods for Reconstructing NDVI Time-Series and Estimating Vegetation Phenology from MODIS Data
Zhanzhang Cai et al.
REMOTE SENSING (2017)
Spectral Information Adaptation and Synthesis Scheme for Merging Cross-Mission Ocean Color Reflectance Observations From MODIS and VIIRS
Kaixu Bai et al.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2016)
Reconstruction of global MODIS NDVI time series: Performance of Harmonic ANalysis of Time Series (HANTS)
Jie Zhou et al.
REMOTE SENSING OF ENVIRONMENT (2015)
Impact of missing data on the estimation of ecological indicators from satellite ocean-colour time-series
Marie-Fanny Racault et al.
REMOTE SENSING OF ENVIRONMENT (2014)
Accuracy and precision in the calculation of phenology metrics
A. Sofia Ferreira et al.
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS (2014)
Monitoring marine phytoplankton seasonality from space
Herve Demarcq et al.
REMOTE SENSING OF ENVIRONMENT (2012)
Inter-comparison of four models for smoothing satellite sensor time-series data to estimate vegetation phenology
Peter M. Atkinson et al.
REMOTE SENSING OF ENVIRONMENT (2012)
A time series for monitoring vegetation activity and phenology at 10-daily time steps covering large parts of South America
Clement Atzberger et al.
INTERNATIONAL JOURNAL OF DIGITAL EARTH (2011)
Phenology of marine phytoplankton from satellite ocean color measurements
M. Vargas et al.
GEOPHYSICAL RESEARCH LETTERS (2009)
Algal blooming patterns and anomalies in the Mediterranean Sea as derived from the SeaWiFS data set (1998-2003)
Vittorio Barale et al.
REMOTE SENSING OF ENVIRONMENT (2008)
Extracting phenological signals from multiyear AVHRR NDVI time series: Framework for applying high-order annual splines with roughness damping
John F. Hermance et al.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2007)
A curve fitting procedure to derive inter-annual phenologies from time series of noisy satellite NDVI data
Bethany A. Bradley et al.
REMOTE SENSING OF ENVIRONMENT (2007)
Stabilizing high-order, non-classical harmonic analysis of NDVI data for average annual models by damping model roughness
J. F. Hermance
INTERNATIONAL JOURNAL OF REMOTE SENSING (2007)
Merging SeaWiFS and MODIS/Aqua ocean color data in North and Equatorial Atlantic using weighted averaging and objective analysis
Claire Pottier et al.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2006)
Variations in satellite-derived phenology in China's temperate vegetation
SL Piao et al.
GLOBAL CHANGE BIOLOGY (2006)
A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky-Golay filter
J Chen et al.
REMOTE SENSING OF ENVIRONMENT (2004)
Monitoring vegetation phenology using MODIS
XY Zhang et al.
REMOTE SENSING OF ENVIRONMENT (2003)
Seasonality extraction by function fitting to time-series of satellite sensor data
P Jönsson et al.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2002)
Decadal changes in global ocean chlorophyll
WW Gregg et al.
GEOPHYSICAL RESEARCH LETTERS (2002)