sptrends: Statistical Inference for Spatiotemporal Trends in Gridded Data

Provides a unified and reproducible framework for statistical inference of spatiotemporal trends in gridded environmental data. The framework addresses the interconnected challenges of serial correlation, spatial dependence and multiple testing that commonly arise when analysing gridded environmental time series. Its core methods support serial-correlation treatment through trend-preserving prewhitening, pixel-wise and spatially explicit trend inference, slope estimation and multiple-testing correction. These methods may be applied independently or integrated within configurable analytical workflows. Dedicated workflows are also provided to reproduce methodologies published in the scientific literature: Gutiérrez-Hernández and García (2025) <doi:10.1016/j.rsase.2024.101377> for the True Significant Trends workflow, Gutiérrez-Hernández and García (2024) <doi:10.3390/rs16203886> for the Robust Trend Analysis workflow, and Gutiérrez-Hernández and García (2025) <doi:10.3390/math13223630> for the adaptive false discovery rate procedure. Supporting utilities facilitate raster data import and inspection, anomaly calculation, spatial autocorrelation diagnostics, simulation studies, benchmarking, visualisation, mapping, and reporting.

Version: 1.6.3
Depends: R (≥ 4.1)
Imports: terra (≥ 1.7-0), Matrix, parallel, stats, utils, graphics, grDevices, withr (≥ 2.2.0)
Suggests: fields, testthat (≥ 3.2.0), knitr, rmarkdown, ncdf4, Kendall, modifiedmk, rkt, robslopes, trend, zyp
Published: 2026-09-22
DOI: 10.32614/CRAN.package.sptrends (may not be active yet)
Author: Oliver Gutiérrez-Hernández ORCID iD [aut, cre] (affiliation: Department of Geography, University of Málaga, Málaga, Spain), Luis V. García ORCID iD [aut] (affiliation: Institute of Natural Resources and Agrobiology of Seville (IRNAS), Spanish National Research Council (CSIC), Seville, Spain)
Maintainer: Oliver Gutiérrez-Hernández <olivergh at uma.es>
BugReports: https://github.com/Olive-r/sptrends/issues
License: GPL (≥ 3)
URL: https://github.com/Olive-r/sptrends, https://olive-r.github.io/sptrends/
NeedsCompilation: no
Language: en-GB
Citation: sptrends citation info
Materials: README, NEWS
CRAN checks: sptrends results

Documentation:

Reference manual: sptrends.html , sptrends.pdf
Vignettes: 0. Loading and exploring spatiotemporal data (source, R code)
1. Dealing with serial correlation (source, R code)
2. Trend inference and statistical significance (source, R code)
3. Trend magnitude estimation (source, R code)
4. Correcting for multiple testing (source, R code)
5. Trend workflows and published methods (source, R code)

Downloads:

Package source: sptrends_1.6.3.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available

Linking:

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