README.md
In donato-morresi/cdmt: Change Detection by Multispectral Trends
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("donatomorresi/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.
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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("donatomorresi/cdmt")
References
Maeng, H. (2019). Adaptive multiscale approaches to regression and trend segmentation. Ph.D. thesis, London School of Economics and Political Science.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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