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TitleAssessment of satellite based vegetation land surface phenology algorithms with application to a 20 year NOAA AVHRR record over Canada and Northern USA
AuthorKandasamy, S; Fernandes, R
SourceIEEE International Geoscience and Remote Sensing Symposium proceedings 6947242, 2014 p. 3522-3525,
Alt SeriesNatural Resources Canada, Contribution Series 20181574
Mediapaper; on-line; digital
File formatpdf
Subjectsgeophysics; Nature and Environment; remote sensing
ProgramClimate Change Geoscience
AbstractLand Surface phenology (LSP) is related to vegetation dynamics and is an indicator of tracking surface climate change. One of the challenges in the study of LSP is the validation of satellite based LSP products. Here, we have proposed a novel methodology of the validating LSP products by applying observed temporal gap and measurement noise to representative daily NDVI reference time series from satellite imagery. Three well-known LSP algorithms(iterative Savitzky-Golay filtering-SGF [1], Asymmetric Gaussian Fitting - AGF [2] and Logistic fitting [3, 4]) are applied to 20 years of NOAA AVHRR measurements over biomes in Canada and Northern USA. For a given AVHRR cloud threshold, both AGF and SGF are more sensitive to the amount of gaps than to the noise in the data.