TSS.RESTREND: Time Series Segmentation of Residual Trends
Time Series Segmented Residual Trends is a method for the automated detection of land degradation from remotely sensed vegetation and climate datasets. TSS-RESTREND incorporates aspects of two existing degradation detection methods: RESTREND which is used to control for climate variability, and BFAST which is used to look for structural changes in the ecosystem. The full details of the testing and justification of the TSS-RESTREND method (version 0.1.02) are published in Burrell et al., (2017). <doi:10.1016/j.rse.2017.05.018>. The changes to the method introduced in version 0.2.03 focus on the inclusion of temperature as an additional climate variable. This allows for land degradation assessment in temperature limited drylands. A paper that details this work is currently under review. There are also a number of bug fixes and speed improvements. Version 0.3.0 introduces additional attribution for eCO2, climate change and climate variability the details of which are in press in Burrell et al., (2020). The version under active development and additional example scripts showing how the package can be applied can be found at <https://github.com/ArdenB/TSSRESTREND>.
||R (≥ 3.6.0)
||stats, graphics, utils, bfast (≥ 1.5.7), broom, strucchange, ggplot2, RcppRoll, mblm
||Arden Burrell [aut, cre]
||Arden Burrell <arden.burrell at gmail.com>
||TSS.RESTREND citation info
Please use the canonical form
to link to this page.