How to cite the R package motif

motif is a popular R package that is available at https://cran.r-project.org/web/packages/motif/index.html. By citing R packages in your paper you lay the grounds for others to be able to reproduce your analysis and secondly you are acknowledging the time and work people have spent creating the package.

APA citation

Formatted according to the APA Publication Manual 7^th edition. Simply copy it to the References page as is.

APA

The minimal requirement is to cite the R package in text along with the version number. Additionally, you can include the reference list entry the authors of the motif package have suggested.

Example of an in-text citation

Analysis of the data was done using the motif package (v0.4.1; Nowosad, 2021).

Reference list entry

Nowosad, J. (2021). Motif: an open-source R tool for pattern-based spatial analysis. Landscape Ecology, 36(1), 29–43.

Vancouver citation

Formatted according to Vancouver style. Simply copy it to the references section as is.

Vancouver

Example of an in-text citation

Analysis of the data was done using the motif package v0.4.1 (1).

Reference list entry

1.
Nowosad J. Motif: an open-source R tool for pattern-based spatial analysis. Landsc Ecol. 2021 Jan;36(1):29–43.

BibTeX

Reference entry in BibTeX format. Simply copy it to your favorite citation manager.

BibTeX

@ARTICLE{Nowosad2021-yz,
  title     = "Motif: an open-source {R} tool for pattern-based spatial
               analysis",
  author    = "Nowosad, Jakub",
  abstract  = "Abstract Context Pattern-based spatial analysis provides methods
               to describe and quantitatively compare spatial patterns for
               categorical raster datasets. It allows for spatial search,
               change detection, and clustering of areas with similar patterns.
               Objectives We developed an R package motif as a set of
               open-source tools for pattern-based spatial analysis. Methods
               This package provides most of the functionality of existing
               software (except spatial segmentation), but also extends the
               existing ideas through support for multi-layer raster datasets.
               It accepts larger-than-RAM datasets and works across all of the
               major operating systems. Results In this study, we describe the
               software design of the tool, its capabilities, and present four
               case studies. They include calculation of spatial signatures
               based on land cover data for regular and irregular areas, search
               for regions with similar patterns of geomorphons, detection of
               changes in land cover patterns, and clustering of areas with
               similar spatial patterns of land cover and landforms.
               Conclusions The methods implemented in motif should be useful in
               a wide range of applications, including land management,
               sustainable development, environmental protection, forest cover
               change and urban growth monitoring, and agriculture expansion
               studies. The motif package homepage is
               https://nowosad.github.io/motif.",
  journal   = "Landsc. Ecol.",
  publisher = "Springer Science and Business Media LLC",
  volume    =  36,
  number    =  1,
  pages     = "29--43",
  month     =  jan,
  year      =  2021,
  url       = "http://dx.doi.org/10.1007/s10980-020-01135-0",
  copyright = "https://creativecommons.org/licenses/by/4.0",
  language  = "en",
  issn      = "0921-2973, 1572-9761",
  doi       = "10.1007/s10980-020-01135-0"
}

RIS

Reference entry in RIS format. Simply copy it to your favorite citation manager.

RIS

TY  - JOUR
AU  - Nowosad, Jakub
TI  - Motif: an open-source R tool for pattern-based spatial analysis
T2  - Landsc. Ecol.
VL  - 36
IS  - 1
SP  - 29-43
PY  - 2021
DA  - 2021/1
PB  - Springer Science and Business Media LLC
AB  - Abstract Context Pattern-based spatial analysis provides methods to
      describe and quantitatively compare spatial patterns for categorical
      raster datasets. It allows for spatial search, change detection, and
      clustering of areas with similar patterns. Objectives We developed an R
      package motif as a set of open-source tools for pattern-based spatial
      analysis. Methods This package provides most of the functionality of
      existing software (except spatial segmentation), but also extends the
      existing ideas through support for multi-layer raster datasets. It accepts
      larger-than-RAM datasets and works across all of the major operating
      systems. Results In this study, we describe the software design of the
      tool, its capabilities, and present four case studies. They include
      calculation of spatial signatures based on land cover data for regular and
      irregular areas, search for regions with similar patterns of geomorphons,
      detection of changes in land cover patterns, and clustering of areas with
      similar spatial patterns of land cover and landforms. Conclusions The
      methods implemented in motif should be useful in a wide range of
      applications, including land management, sustainable development,
      environmental protection, forest cover change and urban growth monitoring,
      and agriculture expansion studies. The motif package homepage is
      https://nowosad.github.io/motif.
SN  - 0921-2973
DO  - 10.1007/s10980-020-01135-0
UR  - http://dx.doi.org/10.1007/s10980-020-01135-0
ER  -

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