Summarize and print the results obtained from the BEAST time series decomposition and segmentation.
## S3 method for class 'beast' print( x, index = 1, ... )
a "beast" object returned by
an integer (default to 1 ) or a vector of two integers to specify the index of the time series to print if
additional parameters to be implemented.
Print a summary of changepoints detected for the seasonal or trend component.
Zhao, K., Wulder, M.A., Hu, T., Bright, R., Wu, Q., Qin, H., Li, Y., Toman, E., Mallick, B., Zhang, X. and Brown, M., 2019. Detecting change-point, trend, and seasonality in satellite time series data to track abrupt changes and nonlinear dynamics: A Bayesian ensemble algorithm. Remote Sensing of Environment, 232, p.111181 (the beast algorithm paper).
Zhao, K., Valle, D., Popescu, S., Zhang, X. and Mallick, B., 2013. Hyperspectral remote sensing of plant biochemistry using Bayesian model averaging with variable and band selection. Remote Sensing of Environment, 132, pp.102-119 (the Bayesian MCMC scheme used in beast).
Hu, T., Toman, E.M., Chen, G., Shao, G., Zhou, Y., Li, Y., Zhao, K. and Feng, Y., 2021. Mapping fine-scale human disturbances in a working landscape with Landsat time series on Google Earth Engine. ISPRS Journal of Photogrammetry and Remote Sensing, 176, pp.250-261(a beast application paper).
library(Rbeast) data(simdata) ## Not run: #out=beast123(simdata) #Error: whichDimIsTime has to be specified to # tell which dim of simdata refers to time. # See below. out=beast123(simdata, metadata=list(whichDimIsTime=1)) print(out, 1) print(out, 2) ## End(Not run)
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