rtsa's Introduction

rtsa

R package for Raster Time Series Analysis

The package provides a collection of analytics to perform spatio-temporal analysis from raster time series. It acts as a front-end to already available functions in various R packages, specifically designed to handle geographic datasets provided as raster time series. The available functions within the package allow the direct input of raster time series to extract concise and comprehensive information. Since some techniques for spatio-temporal analysis can not deal with missing values raster time series, a selection of gap-filling methods are provided.

Main features:

use of raster time series with explicit temporal dimension
use of raster time series as direct input to functions
use of a raster mask to select the region of interest and reduce memory loads
parallel processing using multiple CPUs

Supported gap-filling methods:

DINEOF
linear interpolation
spline interpolation
stine interpolation

Currently, the following analytical methods are supported:

Empirical Orthogonal Function
Empirical Orthogonal Teleconnections
Seasonal Trend Decomposition using Loess
X-11
X-13-ARIMA seasonal adjustment
Mann-Kendall trend test

The following analytical methods will be supported soon:

Self Organizing Maps

Installation

To load (using devtools):

library(devtools)
install_github("marchtaylor/sinkr")
install_github("ffilipponi/rtsa")

Authors

Filipponi Federico

License

Licensed under the GNU General Public License, Version 3.0: https://www.gnu.org/licenses/gpl-3.0.html

Funding

The ECOPOTENTIAL project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 641762

rtsa's People