A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky-Golay filter

By Jin Chen, Per Jönsson, M. Tamura, Z. Gu, B. Matsushita, Lars Eklundh. 2004

2,229 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/5ee037c65be9f0c1b011875163afa2b4daff1527

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecological Modeling

1. Clement Atzberger
2. Peter M. Atkinson
3. Cheryl Stephen Jeganathan
4. J. Dash
5. Ronald E. McRoberts
6. J. F. Hermance
7. Gregory J. McDermid

In Ecology

1. Clement Atzberger
2. Frédéric Baret
3. Xinghua Li
4. B. Wilson
5. Ronald E. McRoberts
6. Joseph F. Knight
7. Chao Zeng
8. Huanfeng Shen

In Global and Planetary Change

1. Clement Atzberger
2. B. Wilson
3. Ronald E. McRoberts
4. Joseph F. Knight
5. Cheryl Stephen Jeganathan
6. J. Dash
7. Peter M. Atkinson
8. Joshua B. Fisher

Citations in the corpus

• Forecasting vegetation condition for drought early warning systems in pastoral communities in Kenya (2019, background): “Following [44] and [45], the polynomial order was set to 2 (i.”
• Stabilizing high‐order, non‐classical harmonic analysis of NDVI data for average annual models by damping model roughness (2007, methodology): “…been recognized that a perennial problem with using conventional Fourier methods is that the higher order terms in a Fourier series needed to capture shorter period fluctuations often generate spurious parasitic oscillations in the modelled response (Jonsson and Eklundh 2002, Chen et al. 2004).”
• Disentangling climatic and anthropogenic controls on global terrestrial evapotranspiration trends (2015, methodology): “…information, used to mask the monthly ET between 1982 and 2010, was first determined from the global inventory modeling andmapping studies normalized difference vegetation index (NDVI3g) dataset (Pinzon and Tucker 2014) using a Savitzky–Golay filter (Chen et al 2004, Jonsson and Eklundh 2004).”
• Harmonic regression of Landsat time series for modeling attributes from national forest inventory data (2018, methodology): “Alternative methods for describing AVHRR time series data have been proposed, using models such as the asymmetric Gaussian (Jönsson and Eklundh, 2002) and the Savitzky-Golay filter (Chen et al., 2004).”
• Missing Information Reconstruction of Remote Sensing Data: A Technical Review (2015, methodology): “1) Sliding Window Filter Methods: These methods are designed to filter in sliding windows, according to certain criteria, and are primarily used for reconstructing NDVI time-series data [48], [51–54].”
• An evaluation of time-series smoothing algorithms for land-cover classifications using MODIS-NDVI multi-temporal data (2016, methodology): “Chen et al. (2004) modified the Savitzky–Golay filter to adapt to the upper envelope of the vegetation index data; an adaptation especially important because NDVI signals are often negatively biased.”