R package rgdal: Bindings for the Geospatial Data Abstraction Library. Provides bindings to Frank Warmerdam’s Geospatial Data Abstraction Library (GDAL) (>= 1.6.3) and access to projection/transformation operations from the PROJ.4 library. The GDAL and PROJ.4 libraries are external to the package, and, when installing the package from source, must be correctly installed first. Both GDAL raster and OGR vector map data can be imported into R, and GDAL raster data and OGR vector data exported. Use is made of classes defined in the sp package. Windows and Mac Intel OS X binaries (including GDAL, PROJ.4 and Expat) are provided on CRAN.
Keywords for this software
References in zbMATH (referenced in 11 articles )
Showing results 1 to 11 of 11.
- Lukas W. Lehnert, Hanna Meyer, Wolfgang A. Obermeier, Brenner Silva, Bianca Regeling, Jörg Bendix: Hyperspectral Data Analysis in R: the hsdar Package (2018) arXiv
- Baumer, Benjamin S.; Kaplan, Daniel T.; Horton, Nicholas J.: Modern data science with R (2017)
- Benjamin Taylor and Barry Rowlingson: spatsurv: An R Package for Bayesian Inference with Spatial Survival Models (2017)
- RESSTE Network et al.: Analyzing spatio-temporal data with R: everything you always wanted to know -- but were afraid to ask (2017)
- Sebastian Meyer and Leonhard Held and Michael Höhle: Spatio-Temporal Analysis of Epidemic Phenomena Using the R Package surveillance (2017)
- Aboukhamseen, S.M.; Soltani, A.R.; Najafi, M.: Modelling cluster detection in spatial scan statistics: formation of a spatial Poisson scanning window and an ADHD case study (2016)
- Patrick Brown: Model-Based Geostatistics the Easy Way (2015)
- Quinn Payton; Michael McManus; Marc Weber; Anthony Olsen; Thomas Kincaid: micromap: A Package for Linked Micromaps (2015)
- Tomislav Hengl; Pierre Roudier; Dylan Beaudette; Edzer Pebesma: plotKML: Scientific Visualization of Spatio-Temporal Data (2015)
- Edzer Pebesma: spacetime: Spatio-Temporal Data in R (2012)
- Thibault Laurent; Anne Ruiz-Gazen; Christine Thomas-Agnan: GeoXp: An R Package for Exploratory Spatial Data Analysis (2012)