What question did this study set out to answer?

To introduce the sf package, providing standardized and modern simple feature support for spatial vector data within the R programming environment.

January 1, 2018Insecta mundiOpen Access

Simple Features for R: Standardized Support for Spatial Vector Data

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Authors

EPEdzer PebesmaUniversity of California, Santa Barbara

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Implication

Technical report demonstrates standardized spatial vector data handling in R, highlighting seamless interoperability across modern data science environments.

Key Points

To introduce the sf package, providing standardized and modern simple feature support for spatial vector data within the R programming environment.
Implemented simple features standards directly into native R structures to encode geometric entities such as points, lines, and polygons.
Integrated functionality previously distributed across legacy packages, including sp, rgeos, and rgdal, into a unified interface.
Achieved full capacity for spatial vector operations comparable to the combined workflows of sp, rgeos, and rgdal.
Enabled standardized interoperability connecting R workflows to external spatial databases and geographic information systems.

Cite This Study

Edzer Pebesma (2018) studied this question.

synapsesocial.com/papers/69d7212e3f906f6a06bef3d8 https://doi.org/10.32614/rj-2018-009

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Implication

Technical report demonstrates standardized spatial vector data handling in R, highlighting seamless interoperability across modern data science environments.

Simple Features for R: Standardized Support for Spatial Vector Data

Discussion

Member takes

Implication

Key Points

Cite This Study

Simple Features for R: Standardized Support for Spatial Vector Data

Discussion

Member takes

Implication

Key Points

Cite This Study

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