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SpatialDownscaling

0.1.2Package record

Methods for Spatial Downscaling Using Deep Learning

0packages depend
1.8Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

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.

Changes in 0.1.2
  • Fixed an incorrect year in the DESCRIPTION Date field for CRAN submission.

From NEWS.md in the release

Install

Health

CRAN checks
13OK
Slowest check: 2.1 min · r-oldrel-windows-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 0.1.2
READMEYes · 476 wordsVignettesNoNEWSYes · 100% structured · mentions 0.1.2Citation fileNoWebsitenot declared in DESCRIPTION
Help pages
7
Examples that run
33%2 run in a plain check · 4 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples
100%
Documented parameters
98%
Return-value docs
100%
Help pages citing references
29% with a bibliography file

Downloads

1.8K
CRAN downloads in the past year
Rank #23,349 · ~5/day · ~147/mo
Daily download trend is not available in this view yet.
18730 days
56190 days
1.8K1 year
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Also on59 r2u

Dependencies

Declared dependencies
6 external dependencies (excludes base and recommended)

Installing SpatialDownscaling adds 39 packages (22 with compiled code, 23 MB of source tarballs). Heaviest: keras3 4.6 MB, sp 4.3 MB, tfruns 1.9 MB.

Depends (1)
R >= 4.4.0
LinkingTo (0)
none
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (5)
Author, Maintainer since 0.1.2 (2026), Copyright holder
Releases (1)
  • R
    R 4.6.0 released · 2026-04-24
  • 0.1.2Latest
    2026-01-26 · current release
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2026-01-26
Total releases
1 / 1 yrs
License
GPL-3 OSI
Minimum R
≥ 4.4.0
Bundled data
1.6 MB / 1 file
Download size
1.6 MB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("SpatialDownscaling")
Sipilä, M., Cappello, C., De Iaco, S., Nordhausen, K., & Taskinen, S. (2026). SpatialDownscaling: Methods for Spatial Downscaling Using Deep Learning (Version 0.1.2) [Computer software]. https://doi.org/10.32614/CRAN.package.SpatialDownscaling

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for SpatialDownscaling version 0.1.2 [Data set]. HJJB, LLC. Data release v2026-10-25. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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