R2_sign

Critical value of determined correlation

internal

The merits of 'TIMESAT' and 'phenopix' are adopted. Besides, a simple and
growing season dividing method and a practical snow elimination method
based on Whittaker were proposed. 7 curve fitting methods and 4 phenology
extraction methods were provided. Parameters boundary are considered for
every curve fitting methods according to their ecological meaning.
And 'optimx' is used to select best optimization method for different
curve fitting methods.
Reference:
Kong, D., (2020). R package: A state-of-the-art Vegetation Phenology extraction
package, phenofit version 0.3.1, <doi:10.5281/zenodo.5150204>;
Kong, D., Zhang, Y., Wang, D., Chen, J., & Gu, X. (2020). Photoperiod Explains
the Asynchronization Between Vegetation Carbon Phenology and Vegetation Greenness
Phenology. Journal of Geophysical Research: Biogeosciences, 125(8), e2020JG005636.
<doi:10.1029/2020JG005636>;
Kong, D., Zhang, Y., Gu, X., & Wang, D. (2019). A robust method for reconstructing
global MODIS EVI time series on the Google Earth Engine.
ISPRS Journal of Photogrammetry and Remote Sensing, 155, 13–24;
Zhang, Q., Kong, D., Shi, P., Singh, V.P., Sun, P., 2018. Vegetation phenology
on the Qinghai-Tibetan Plateau and its response to climate change (1982–2013).
Agric. For. Meteorol. 248, 408–417. <doi:10.1016/j.agrformet.2017.10.026>.

Dongdong Kong

phenofit

Extract Remote Sensing Vegetation Phenology

Mingzhong Xiao

Yongqiang Zhang

Xihui Gu

Jianjian Cui

R2_sign function

<dl><dt>n</dt>
<dd>length of observation.</dd>
<dt>NumberOfPredictor</dt>
<dd>Number of predictor, including constant.</dd>
<dt>alpha</dt>
<dd>significant level.</dd></dl>

Arguments

Critical value of determined correlation — R2_sign

<dl>

<dt>n</dt>
<dd>length of observation.</dd>


<dt>NumberOfPredictor</dt>
<dd>Number of predictor, including constant.</dd>


<dt>alpha</dt>
<dd>significant level.</dd>

</dl>

R2_sign: Critical value of determined correlation

Description

Usage

Value

Arguments

References

Examples