A tool for Hierarchical Climate Regionalization applicable to any correlation-based clustering.
It adds several features and a new clustering method (called, 'regional' linkage) to hierarchical
clustering in R ('hclust' function in 'stats' library): data regridding, coarsening spatial resolution,
geographic masking, contiguity-constrained clustering, data filtering by mean and/or variance
thresholds, data preprocessing (detrending, standardization, and PCA), faster correlation function
with preliminary big data support, different clustering methods, hybrid hierarchical clustering,
multivariate clustering (MVC), cluster validation, visualization of regionalization results, and
exporting region map and mean timeseries into NetCDF-4 file.
graphics, grDevices, stats, utils, ncdf4

c(
person(given = "Hamada S.",
family = "Badr",
email = "badr@jhu.edu",
role = c("aut", "cre"),
comment = c(ORCID = "0000-0002-9808-2344")),
person(given = "Amin K.",
family = "Dezfuli",
email = "amin.dezfuli@nasa.gov",
role = c("aut"),
comment = c(ORCID = "0000-0003-3274-8542")),
person(given = "Benjamin F.",
family = "Zaitchik",
email = "zaitchik@jhu.edu",
role = c("aut"),
comment = c(ORCID = "0000-0002-0698-0658")))

c(
person(given = "Hamada S.",
family = "Badr",
email = "badr@jhu.edu",
role = c("aut", "cre"),
comment = c(ORCID = "0000-0002-9808-2344")),
person(given = "Benjamin F.",
family = "Zaitchik",
email = "zaitchik@jhu.edu",
role = c("aut"),
comment = c(ORCID = "0000-0002-0698-0658")),
person(given = "Amin K.",
family = "Dezfuli",
email = "amin.dezfuli@nasa.gov",
role = c("aut"),
comment = c(ORCID = "0000-0003-3274-8542")))
A tool for Hierarchical Climate Regionalization applicable to any correlation-based clustering.
It adds several features and a new clustering method (called, 'regional' linkage) to hierarchical
clustering in R ('hclust' function in 'stats' library): data regridding, coarsening spatial resolution,
geographic masking, contiguity-constrained clustering, data filtering by mean and/or variance
thresholds, data preprocessing (detrending, standardization, and PCA), faster correlation function
with preliminary big data support, different clustering methods, hybrid hierarchical clustering,
multivariate clustering (MVC), cluster validation, visualization of regionalization results, and
exporting region map and mean timeseries into NetCDF-4 file.
The technical details are described in the paper by Hamada S. Badr, Benjamin F. Zaitchik, and
Amin K. Dezfuli (2015) <doi:10.1007/s12145-015-0221-7>.