In donato-morresi/cdmt: Change Detection by Multispectral Trends

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Change Detection by Multispectral Trends (CDMT)

About

The cdmt R package provides an implementation of CDMT, which is a Landsat time series-based algorithm for mapping inter-annual changes in linear trends at the pixel level. CDMT was designed to detect abrupt and gradual spectral changes associated with forest disturbance dynamics. A detailed description of the algorithm will be provided in an upcoming paper. Landsat time series can be univariate, i.e. include a single spectral band/index, or multivariate, i.e. include multiple spectral bands/indices. A modified version of the High Dimensional Trend Segmentation (HiTS) procedure proposed by Maeng (2019) is at the core of CDMT. cdmt relies on the terra package for managing raster data and parallelising computations.

Installation

You can install the development version of cdmt with:

# install.packages("devtools")
devtools::install_github("donato-morresi/cdmt")

References

Maeng, H. (2019). Adaptive multiscale approaches to regression and trend segmentation. Ph.D. thesis, London School of Economics and Political Science.

donato-morresi/cdmt documentation built on June 15, 2022, 9:54 a.m.