PhenoKl: A function to extract phenological thresholds according to...

In phenopix: Process Digital Images of a Vegetation Cover

Description

A function to extract phenological thresholds according to Klosterman et al. 2014. This is a rather internal function. Use PhenoExtract with method='klosterman' instead.

Usage

PhenoKl(x, uncert = FALSE, fit, breaks, ...)

Arguments

x	A named vector with the parameters of the equation used to fit the data.
uncert	Currently unused
fit	A list structured as in output from the fitting procedures, such as GuFit, KlostermanFit, ElmoreFit, BeckFit.
breaks	Currently unused
...	Further arguments, currently not used.

Details

Threshold extraction is performed according to Klosterman et al (2014) with a modification derived from Zhang et al (2003). Briefly, the rate of curvature (k) as defined in Klosterman et al (2014) is computed and inflection points are evaluated on its derivative (derK). The growing season is splitted in its increasing and decreasing parts around the maximum. The same happens to derK. Greenup date is defined as the day of maximum derK (a local maximum) before the first minimum in derK in the increasing part of the curve. Maturity is defined as the maximum in derK between the minimum of derK and mid season. Senescence is defined as the first local minimum in the decreasing part of derK. Dormancy is defined as the last local minimum in derK. Phases are named after Zhang et al (2003).

Value

A named vector of length 4 with the extracted thresholds: Greenup, Maturity, Senescence, Dormancy.

Note

Since this threshold extraction is based on a derivable function, it cannot be performed on raw data. Uncertainty estimation with this method on a fitted curve from SplineFit is currently not implemented. Instead you can use PhenoKl in a for loop cycling in the uncertainty dataframe columns.

Author(s)

Gianluca Filippa <[e-mail]>

References

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.

See Also

PhenoExtract

Examples

data(bartlett2009.fitted)
klosterman.phenophases <- PhenoKl(
	x=bartlett2009.fitted$fit$params, 
	fit=bartlett2009.fitted$fit)
plot(bartlett2009.fitted$fit$predicted)
abline(v=klosterman.phenophases[1:4], col=palette())
mtext(names(klosterman.phenophases[1:4]), 
	at=klosterman.phenophases[1:4], line=-2:-5, 
	col=palette()[1:4])

Example output

phenopix documentation built on May 2, 2019, 4:50 p.m.