greenProcess: Fit a curve and extract thresholds from vegetation index time...

In phenopix: Process Digital Images of a Vegetation Cover

Fit a curve and extract thresholds from vegetation index time series

Description

This is a wrapper function that calls fitting functions and threshold functions and returns an object of class phenopix.

Usage

greenProcess(ts, fit, threshold=NULL, plot=TRUE, which='light', 
  uncert=FALSE, nrep=100, 
  envelope='quantiles', quantiles=c(0.1, 0.9), hydro=FALSE, 
  sf=quantile(ts, na.rm=TRUE, prob=c(0.05, 0.95)), ncores='all', ...)

Arguments

ts	A vector or, better, an univariate ts or zoo object.
fit	A character vector of length 1. Available options are: spline, beck, elmore, klosterman, gu.
threshold	A character vector of length 1. Available options are: trs, derivatives, klosterman, gu.
plot	If TRUE a call to PhenoPlot returns fitted values and thresholds.
which	Only relevant if fit == klosterman, available options are light or heavy. See FitDoubleLogKlHeavy and FitDoubleLogKlLight for details.
uncert	Should uncertainty be estimated?
nrep	Number of replications for the uncertainty estimation.
envelope	One between quantiles and min-max. If quantiles, the uncertainty envelope will be computed as quantiles. Quantiles reported in quantiles will be computed togheter with the median. If min-max is choosen, min, max and mean of the uncertainty envelope will be returned.
quantiles	Quantiles to be calculated if envelope='quantiles'. The notation is the same as to specify quantiles in the quantile function, i.e. to get 10th and 90th percentile, use c(0.1, 0.9).
hydro	Hydro determines how days of the year are computed. If hydro = FALSE (default) January 1st is DOY 1. If hydro = TRUE October 1st is day 1. This option has been introduced for two purposes. First, for water limited or high temperature limited boreal ecosystems (with summer dormant season) to process a seasonal trajectory with winter peak. Second, for ecosystems in the australian emisphere. If hydro = TRUE all metrics concerned with a day of year must be back converted in order to get actual day of year. Conversions and back conversions can be performed with the function doy2hydrodoy.
sf	Scaling factors used instead of min and max for data normalization.
ncores	Number of processors to be used in parallel computation, defaults to 'all' which will accidentally slow down any other activity on your computer. Otherwise set the number of processors you want to use in parallelization.
...	For the plotting function, a number of parameters from generic plot can be specified. See examples.

Details

This function is a wrapper function that allows to fit a curve to a yearly trajectories of greeneess and extract phenological thresholds according to a given criterion. Handeling this main function may allow the user to forget learning other, rather internal functions. The combination of greenProcess and extract allows to use main capabilities of this package. Virtually all other functions included are called at some points within this function. The object of class phenopix which is created is a rather complex list that can be explored via the extract function. Check it out for further details.

Value

An object of class phenopix with dedicated functions: plot(), print(), summary() and fitted(). The structure is actually a list.

Author(s)

Gianluca Filippa <[e-mail]>

References

Gu L, Post WM, Baldocchi D, Black TA, Suyker AE, Verma SB, Vesala T, Wofsy SC. (2009) Characterizing the Seasonal Dynamics of Plant Community Photosynthesis Across a Range of Vegetation Types. In: Phenology of Ecosystem Processes (Ed: Noormets A, Springer New York), pp 35-58.

Klosterman ST, Hufkens K, Gray JM, Melaas E, Sonnentag O, Lavine I, Mitchell L, Norman R, Friedl MA, Richardson A D (2014) Evaluating remote sensing of deciduous forest phenology at multiple spatial scales using PhenoCam imagery, Biogeosciences, 11, 4305-4320, doi:10.5194/bg-11-4305-2014.

Zhang X, Friedl MA, Schaaf CB, Strahler AH, Hodges JCF, Gao F, Reed BC, Huete A (2003) Monitoring vegetation phenology using MODIS, Remote Sens. Environ., 84, 471-475.

Examples

## Not run: 
data(bartlett2009.filtered)
fitted <- greenProcess(bartlett2009.filtered, 'klosterman', 
  'klosterman', uncert=TRUE, nrep=5, ncores=2)
  
## End(Not run)

phenopix documentation built on Aug. 9, 2023, 5:10 p.m.