rgdal

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.


References in zbMATH (referenced in 23 articles )

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  1. Ann-Kristin Kreutzmann; Sören Pannier; Natalia Rojas-Perilla; Timo Schmid; Matthias Templ; Nikos Tzavidis: The R Package emdi for Estimating and Mapping Regionally Disaggregated Indicators (2019) not zbMATH
  2. Davis, Benjamin J. K.; Curriero, Frank C.: Development and evaluation of geostatistical methods for non-Euclidean-based spatial covariance matrices (2019)
  3. Gianmarco Alberti: movecost: An R package for calculating accumulated slope-dependent anisotropic cost-surfaces and least-cost paths (2019) not zbMATH
  4. Mihai Tivadar: OasisR: An R Package to Bring Some Order to the World of Segregation Measurement (2019) not zbMATH
  5. Victor Maus and Gilberto Câmara and Marius Appel and Edzer Pebesma: dtwSat: Time-Weighted Dynamic Time Warping for Satellite Image Time Series Analysis in R (2019) not zbMATH
  6. Ferreira, Guillermo; Mateu, Jorge; Porcu, Emilio: Spatio-temporal analysis with short- and long-memory dependence: a state-space approach (2018)
  7. Lukas W. Lehnert, Hanna Meyer, Wolfgang A. Obermeier, Brenner Silva, Bianca Regeling, Jörg Bendix: Hyperspectral Data Analysis in R: the hsdar Package (2018) arXiv
  8. Martijn Tennekes: tmap: Thematic Maps in R (2018) not zbMATH
  9. Roman Luštrik; Žan Kuralt: wolfexplorer: a tool for visualization and exploration of complex multi-year multi-specimen datasets (2018) not zbMATH
  10. Baumer, Benjamin S.; Kaplan, Daniel T.; Horton, Nicholas J.: Modern data science with R (2017)
  11. Benjamin Taylor and Barry Rowlingson: spatsurv: An R Package for Bayesian Inference with Spatial Survival Models (2017) not zbMATH
  12. Carracedo, Patricia; Debón, Ana: Spatial statistical tools to assess mortality differences in Europe (2017)
  13. RESSTE Network; et al.: Analyzing spatio-temporal data with R: everything you always wanted to know -- but were afraid to ask (2017)
  14. Sebastian Meyer and Leonhard Held and Michael Höhle: Spatio-Temporal Analysis of Epidemic Phenomena Using the R Package surveillance (2017) not zbMATH
  15. 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)
  16. Patrick Brown: Model-Based Geostatistics the Easy Way (2015) not zbMATH
  17. Quinn Payton; Michael McManus; Marc Weber; Anthony Olsen; Thomas Kincaid: micromap: A Package for Linked Micromaps (2015) not zbMATH
  18. Tomislav Hengl; Pierre Roudier; Dylan Beaudette; Edzer Pebesma: plotKML: Scientific Visualization of Spatio-Temporal Data (2015) not zbMATH
  19. Edzer Pebesma: spacetime: Spatio-Temporal Data in R (2012) not zbMATH
  20. Thibault Laurent; Anne Ruiz-Gazen; Christine Thomas-Agnan: GeoXp: An R Package for Exploratory Spatial Data Analysis (2012) not zbMATH

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