# ------------------------------------------------
# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# ------------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "sptrends" in publications use:'
type: software
license: GPL-3.0-or-later
title: 'sptrends: Statistical Inference for Spatiotemporal Trends in Gridded Data'
version: 1.6.3
doi: 10.5281/zenodo.21822842
identifiers:
- type: doi
  value: 10.32614/CRAN.package.sptrends
abstract: '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) <https://doi.org/10.1016/j.rsase.2024.101377>
  for the True Significant Trends workflow, Gutiérrez-Hernández and García (2024)
  <https://doi.org/10.3390/rs16203886> for the Robust Trend Analysis workflow, and
  Gutiérrez-Hernández and García (2025) <https://doi.org/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.'
authors:
- family-names: Gutiérrez-Hernández
  given-names: Oliver
  email: olivergh@uma.es
  orcid: https://orcid.org/0000-0003-2580-5465
  affiliation: Department of Geography
- family-names: García
  given-names: Luis V.
  orcid: https://orcid.org/0000-0002-5514-2941
  affiliation: Institute of Natural Resources and Agrobiology of Seville (IRNAS)
preferred-citation:
  type: manual
  title: 'sptrends: Statistical Inference for Spatiotemporal Trends in Gridded Data'
  authors:
  - family-names: Gutiérrez-Hernández
    given-names: Oliver
    orcid: https://orcid.org/0000-0003-2580-5465
    email: olivergh@uma.es
    affiliation: Department of Geography
  - family-names: García
    given-names: Luis V.
    orcid: https://orcid.org/0000-0002-5514-2941
    affiliation: Institute of Natural Resources and Agrobiology of Seville (IRNAS)
  year: '2026'
  notes: R package
  doi: 10.5281/zenodo.21822842
  url: https://doi.org/10.5281/zenodo.21822842
repository: https://olive-r.r-universe.dev
repository-code: https://github.com/Olive-r/sptrends
commit: 4c3413de8dd2efe86edeb7ffad4c9aa655313436
url: https://olive-r.github.io/sptrends/
date-released: '2026-10-10'
contact:
- family-names: Gutiérrez-Hernández
  given-names: Oliver
  email: olivergh@uma.es
  orcid: https://orcid.org/0000-0003-2580-5465
  affiliation: Department of Geography
references:
- type: article
  title: Uncovering true significant trends in global greening
  authors:
  - family-names: Gutiérrez-Hernández
    given-names: Oliver
    orcid: https://orcid.org/0000-0003-2580-5465
  - family-names: García
    given-names: Luis V.
    orcid: https://orcid.org/0000-0002-5514-2941
  journal: 'Remote Sensing Applications: Society and Environment'
  year: '2025'
  volume: '37'
  issn: 2352-9385
  doi: 10.1016/j.rsase.2024.101377
  start: '101377'
- type: article
  title: 'Robust Trend Analysis in Environmental Remote Sensing: A Case Study of Cork
    Oak Forest Decline'
  authors:
  - family-names: Gutiérrez-Hernández
    given-names: Oliver
    orcid: https://orcid.org/0000-0003-2580-5465
  - family-names: García
    given-names: Luis V.
    orcid: https://orcid.org/0000-0002-5514-2941
  journal: Remote Sensing
  year: '2024'
  volume: '16'
  issue: '20'
  doi: 10.3390/rs16203886
  start: '3886'