---
title: "raster (R package): papers citing this CRAN package"
description: "8 papers in the tracked journals link to raster (R package) in their Crossref records, the first in 2017; most of them (2) in 2018."
url: https://scholar4ai.com/code/cran-raster
markdown_url: https://scholar4ai.com/code/cran-raster.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "8 papers in the tracked journals link to raster (R package) in their Crossref records, the first in 2017; most of them (2) in 2018. (as of 2026-11-03)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-03T14:43:26+09:00
window: 2026-10-05 to 2026-11-03
source: OpenAlex (CC0)
---

# raster (R package): papers linking to it

Research papers in the 480 tracked journals that link to raster (R package) (https://CRAN.R-project.org/package=raster), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

- CRAN
- https://CRAN.R-project.org/package=raster

All repositories: https://scholar4ai.com/code.md

## Key findings

- 8 papers in the tracked journals link to raster (R package) in their Crossref records, the first in 2017; most of them (2) in 2018.
- By category: Economics (3), AI (3) and Higher Education and Research (1); the journals with the most are Land Use Policy (3), Journal Of Big Data (2) and Scientometrics (1).

## By year

*Papers linking to raster (R package) by publication year*

| Year | Papers |
|---|---:|
| 2017 | 1 |
| 2018 | 2 |
| 2019 | 1 |
| 2020 | 1 |
| 2023 | 1 |
| 2024 | 1 |
| 2025 | 1 |

## Journals

*Journals whose papers link to raster (R package) most*

| Journal | Papers |
|---|---:|
| [Land Use Policy](https://scholar4ai.com/journals/land-use-policy.md) | 3 |
| [Journal Of Big Data](https://scholar4ai.com/journals/journal-of-big-data.md) | 2 |
| [Scientometrics](https://scholar4ai.com/journals/scientometrics.md) | 1 |
| [Knowledge and Information Systems](https://scholar4ai.com/journals/knowledge-and-information-systems.md) | 1 |
| [Spatial Statistics](https://scholar4ai.com/journals/spatial-statistics.md) | 1 |

## Papers

*Papers linking to raster (R package), most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2017-05-04 | [Sustainable recommendation domains for scaling agricultural technologies in Tanzania](https://doi.org/10.1016/j.landusepol.2017.04.028) | [Land Use Policy](https://scholar4ai.com/journals/land-use-policy.md) | Francis Muthoni, Zhe Guo, Mateete A. Bekunda et al. | 31 | cites it |
| 2018-07-08 | [Why do ecologists search for co-authorships? Patterns of co-authorship networks in ecology (1977–2016)](https://doi.org/10.1007/s11192-018-2835-2) | [Scientometrics](https://scholar4ai.com/journals/scientometrics.md) | Anderson Matos Medina | 14 | cites it |
| 2023-10-18 | [Quality of interaction-based predictive model for support of online learning in pandemic situations](https://doi.org/10.1007/s10115-023-01995-3) | [Knowledge and Information Systems](https://scholar4ai.com/journals/knowledge-and-information-systems.md) | Faiza Mumtaz, Ali Imran Jehangiri, Waqar Ishaq et al. | 11 | cites it |
| 2019-03-22 | [Bayesian mixture models and their Big Data implementations with application to invasive species presence-only data](https://doi.org/10.1186/s40537-019-0188-1) | [Journal Of Big Data](https://scholar4ai.com/journals/journal-of-big-data.md) | Insha Ullah, Kerrie Lee Mengersen | 6 | cites it |
| 2020-07-31 | [Stochastic spatial random forest (SS-RF) for interpolating probabilities of missing land cover data](https://doi.org/10.1186/s40537-020-00331-8) | [Journal Of Big Data](https://scholar4ai.com/journals/journal-of-big-data.md) | Jacinta Holloway, Kate J. Helmstedt, Kerrie Lee Mengersen | 6 | cites it |
| 2018-04-21 | [Spatial detrending revisited: Modelling local trend patterns in NO2-concentration in Belgium and Germany](https://doi.org/10.1016/j.spasta.2018.04.004) | [Spatial Statistics](https://scholar4ai.com/journals/spatial-statistics.md) | Svenia Behm, Harry Haupt, A. Schmid | 5 | cites it |
| 2024-09-23 | [Structured decision-making shows broad support from diverse stakeholders for habitat conservation and restoration in Kenya’s Central Highlands](https://doi.org/10.1016/j.landusepol.2024.107364) | [Land Use Policy](https://scholar4ai.com/journals/land-use-policy.md) | Gwili E. M. Gibbon, Martin Dallimer, Hassan Golo et al. | 2 | cites it |
| 2025-10-15 | [Spatial modeling of urban expansion for the territorial management of Ilha Comprida – Brazil](https://doi.org/10.1016/j.landusepol.2025.107805) | [Land Use Policy](https://scholar4ai.com/journals/land-use-policy.md) | Hedla Mendonça Andrade, Ângela Terumi Fushita, Vitor Vieira Vasconcelos | 0 | cites it |

## How this is measured

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

## Cite this page

Scholar4AI. (2026). raster (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-raster

```bibtex
@misc{scholar4ai-code-cran-raster,
  author = {{Scholar4AI}},
  title = {raster (R package): papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/cran-raster}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).