sta-package {sta} | R Documentation |
Statistical Trend Analysis (STA) for Time Series of Satellite Imagery
Description
STA applies the Mann-Kendall test for trend to the so-called shape parameters
of periodic time series. STA estimates shape parameters via harmonic regression.
STA can handle numeric
time series and RasterStack
of satellite images.
Details
Shape parameters is the term used in vegetation monitoring to refer to the amplitudes and phase angles resulting from fitting a harmonic regression model to time series of vegetation indices derived from satellite images. Regardless of its origin, STA can be applied to any periodic time series which makes this package potentially useful to other disciplines such as hydrology, climatology and econometrics.
With sta
(the main function of this package) it is possible to perform
the Mann-Kendall test for trend on time series of the three most commonly used
shape parameters: mean, annual and semiannual. These parameters
are the estimated amplitude coefficients of the aforementioned harmonic regresion
model. This function allows parallel processing to handle large satellite time series
imagery.
STA includes the following graphical methods:
-
plot.staNumeric
: generic plot displayingsta
's output for numeric time series. -
plot.staMatrix
: maps ofmapview-class
displayingsta
's output forRasterStack
.
STA include the following datasets:
-
marismas
: numeric vector containing 10-day Composite NDMI values from 2000 to 2018. -
ndmi
:RasterStack
containing 612 spatial subsets of 10-day Composite NDMI images acquired from 2001 to 2017.
Author(s)
Tecuapetla-Gómez, I. itecuapetla@conabio.gob.mx
References
Eastman, R., Sangermano, F., Ghimire, B., Zhu, H., Chen, H., Neeti, N., Cai, Y., Machado, E., Crema, S. (2009). Seasonal trend analysis of image time series, International Journal of Remote Sensing 30(10), 2721–2726.