| Title | Assessment of satellite based vegetation land surface phenology algorithms with application to a 20 year NOAA AVHRR record over Canada and Northern USA |
| |
| Author | Kandasamy, S ;
Fernandes, R |
| Source | IEEE International Geoscience and Remote Sensing Symposium proceedings 2014, 6947242, 2014 p. 3522-3525, https://doi.org/10.1109/IGARSS.2014.6947242 |
| Year | 2014 |
| Alt Series | Natural Resources Canada, Contribution Series 20181574 |
| Publisher | IEEE |
| Document | serial |
| Lang. | English |
| Media | paper; on-line; digital |
| File format | pdf |
| Area | Canada; United States of America |
| Subjects | geophysics; environmental geology; Nature and Environment; Science and Technology; remote sensing; satellite imagery; climate effects; vegetation; Climate change |
| Program | Remote Sensing Science |
| Released | 2014 11 06 |
| Abstract | 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. |
| GEOSCAN ID | 311929 |
|
|