Package: SpatialDownscaling
Type: Package
Title: Methods for Spatial Downscaling Using Deep Learning
Version: 0.1.2
Date: 2026-01-21
Authors@R: c(person(given = "Mika", family = "Sipilä", role = c("aut", "cre", "cph"), email = "mika.e.sipila@jyu.fi", comment=c(ORCID = "0000-0002-5912-840X")),
             person(given = "Claudia", family = "Cappello", role = c("aut"), email = "claudia.cappello@unisalento.it", comment=c(ORCID = "0000-0002-7905-5068")),
             person(given = "Sandra", family = "De Iaco", role = c("aut"), email = "sandra.deiaco@unisalento.it", comment=c(ORCID = "0000-0003-1820-2068")),
             person(given = "Klaus", family = "Nordhausen", role = c("aut"), email = "klaus.nordhausen@helsinki.fi", comment=c(ORCID = "0000-0002-3758-8501")),
             person(given = "Sara", family = "Taskinen", role = c("aut"), email = "sara.l.taskinen@jyu.fi", comment=c(ORCID = "0000-0001-9470-7258")))
Imports: stats, tensorflow, keras3, magrittr, Rdpack, raster, abind
Description: The aim of the spatial downscaling is to increase the
        spatial resolution of the gridded geospatial input data. This
        package contains two deep learning based spatial downscaling
        methods, super-resolution deep residual network (SRDRN) (Wang
        et al., 2021 <doi:10.1029/2020WR029308>) and UNet (Ronneberger
        et al., 2015 <doi:10.1007/978-3-319-24574-4_28>), along with a
        statistical baseline method bias correction and spatial
        disaggregation (Wood et al., 2004
        <doi:10.1023/B:CLIM.0000013685.99609.9e>). The SRDRN and UNet
        methods are implemented to optionally account for cyclical
        temporal patterns in case of spatio-temporal data. For more
        details of the methods, see Sipilä et al. (2025)
        <doi:10.48550/arXiv.2512.13753>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RdMacros: Rdpack
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
SystemRequirements: Python (>= 3.8), TensorFlow, Keras
Depends: R (>= 4.4.0)
Config/pak/sysreqs: libgdal-dev gdal-bin libgeos-dev libpng-dev
        libproj-dev python3 libsqlite3-dev
Repository: https://mikasip.r-universe.dev
Date/Publication: 2026-09-10 06:38:15 UTC
RemoteUrl: https://github.com/mikasip/spatialdownscaling
RemoteRef: HEAD
RemoteSha: c409006e5e8453d6d6dcf83961d51ae85904131f
NeedsCompilation: no
Packaged: 2026-11-01 08:39:28 UTC; root
Author: Mika Sipilä [aut, cre, cph] (ORCID:
    <https://orcid.org/0000-0002-5912-840X>),
  Claudia Cappello [aut] (ORCID: <https://orcid.org/0000-0002-7905-5068>),
  Sandra De Iaco [aut] (ORCID: <https://orcid.org/0000-0003-1820-2068>),
  Klaus Nordhausen [aut] (ORCID: <https://orcid.org/0000-0002-3758-8501>),
  Sara Taskinen [aut] (ORCID: <https://orcid.org/0000-0001-9470-7258>)
Maintainer: Mika Sipilä <mika.e.sipila@jyu.fi>