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Seasonality extraction by function fitting to time-series of satellite sensor data
Abstract
A new method for extracting seasonality information from time-series of satellite sensor data is presented. The method is based on nonlinear least squares fits of asymmetric Gaussian model functions to the time-series. The smooth model functions are then used for defining key seasonality parameters, such as the number of growing seasons, the beginning and end of the seasons, and the rates of growth and decline. The method is implemented in a computer program TIMESAT and tested on Advanced Very High Resolution Radiometer (AVHRR) normalized difference vegetation index (NDVI) data over Africa. Ancillary cloud data [clouds from AVHRR (CLAVR)] are used as estimates of the uncertainty levels of the data values. Being general in nature, the proposed method can be applied also to new types of satellite-derived time-series data.
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Cited by
Cai, Y., Guan, K., Peng, J., Wang, S., Seifert, C., Wardlow, B., & Li, Z. (2018) · Remote Sensing of Environment · doi:10.1016/j.rse.2018.02.045 · Cited by 540
Zhao, K., Wulder, M. A., Hu, T., Bright, R., Wu, Q., Qin, H., Li, Y., Toman, E., Mallick, B., Zhang, X., et al. (2019) · Remote Sensing of Environment · doi:10.1016/j.rse.2019.04.034 · Cited by 514
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Metadata
- Authors
- Jonsson, P., & Eklundh, L.
- Venue
- IEEE Transactions on Geoscience and Remote Sensing
- Published
- 2002-08
- Volume
- 40
- Issue
- 8
- Pages
- 1824-1832
- ISSN
- 0196-2892 (ISSN-L)
- OpenAlex
- W2113503197
- Cited by
- 1,272
- References
- 0
- FWCI
- 4.87
- Type
- journal article
- Language
- en
- Open access
- closed
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- Jonsson, P., & Eklundh, L. (2002). Seasonality extraction by function fitting to time-series of satellite sensor data. IEEE Transactions on Geoscience and Remote Sensing. https://doi.org/10.1109/tgrs.2002.802519
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