Assessment of satellite based vegetation land surface phenology algorithms with application to a 20 year NOAA AVHRR record over Canada and Northern USA

被引：0

作者：

Kandasamy, Sivasathivel ^{[1
]}

Fernandes, Richard ^{[1
]}

机构：

[1] Canada Ctr Remote Sensing, Nat Resources Canada, Ottawa, ON K1S 5K2, Canada

来源：

2014 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2014年

关键词：

time series; phenology; comparison; validation; TIME-SERIES DATA; MODIS;

D O I：

10.1109/IGARSS.2014.6947242

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Land 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.

引用

页码：3522 / 3525

页数：4

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