Bindings to the GDAL API

gdalraster is an interface to the Geospatial Data Abstraction Library (GDAL) providing an R implementation of the GDAL Raster and Vector Data Models. Bindings also include the GDAL Geometry API, Spatial Reference Systems API, utilities and algorithms, methods for coordinate transformation, and the Virtual Systems Interface (VSI) API. Calling signatures resemble those of the native C, C++ and Python APIs provided by the GDAL project. See https://gdal.org/en/stable/api/ for details of the GDAL API.

Details

Core raster functionality is contained in class GDALRaster and several related stand-alone functions:

• GDALRaster-class is an exposed C++ class that allows opening a raster dataset and calling methods on the GDALDataset, GDALDriver and GDALRasterBand objects in the underlying API (e.g., get/set parameters, read/write pixel data).

• raster creation: create(), createCopy(), rasterFromRaster(), translate(), getCreationOptions(), validateCreationOptions()

• virtual raster: autoCreateWarpedVRT(), buildVRT(), rasterToVRT()

• reproject/resample/crop/mosaic: warp()

• algorithms: dem_proc(), fillNodata(), footprint(), polygonize(), rasterize(), sieveFilter(), GDALRaster$getChecksum()

• raster attribute tables: buildRAT(), displayRAT(), GDALRaster$getDefaultRAT(), GDALRaster$setDefaultRAT()

• geotransform conversion: apply_geotransform(), get_pixel_line(), inv_geotransform(), pixel_extract()

• data type convenience functions: dt_size(), dt_is_complex(), dt_is_integer(), dt_is_floating(), dt_is_signed(), dt_union(), dt_union_with_value(), dt_find(), dt_find_for_value()

Core vector functionality is contained in class GDALVector and several related stand-alone functions:

• GDALVector-class is an exposed C++ class that allows opening a vector dataset and calling methods on a specified OGRLayer object that it contains (e.g., obtain layer information, set attribute and/or spatial filters, read/write feature data).

• OGR vector utilities: ogrinfo(), ogr2ogr(), ogr_reproject(), ogr_define, ogr_manage, ogr_proc()

Bindings to the GDAL Geometry API, Spatial Reference Systems API, methods for coordinate transformation, the Virtual Systems Interface (VSI) API, general data management and system configuration are implemented in several stand-alone functions:

• Geometry API: bbox_from_wkt(), bbox_to_wkt(), bbox_intersect(), bbox_union(), bbox_transform(), g_factory, g_query, g_binary_pred, g_binary_op, g_measures, g_unary_op, g_coords(), g_envelope(), g_make_valid(), g_swap_xy(), g_transform(), g_wk2wk(), geos_version()

• Spatial Reference Systems API: srs_convert, srs_query

• coordinate transformation: transform_xy(), inv_project(), transform_bounds()

• data management: addFilesInZip(), copyDatasetFiles(), deleteDataset(), renameDataset(), bandCopyWholeRaster(), identifyDriver(), inspectDataset()

• Virtual Systems Interface API: VSIFile-class, vsi_clear_path_options(), vsi_copy_file(), vsi_curl_clear_cache(), vsi_get_disk_free_space(), vsi_get_file_metadata(), vsi_get_fs_options(), vsi_get_fs_prefixes(), vsi_is_local(), vsi_mkdir(), vsi_read_dir(), vsi_rename(), vsi_rmdir(), vsi_set_path_option(), vsi_stat(), vsi_supports_rnd_write(), vsi_supports_seq_write(), vsi_sync(), vsi_unlink(), vsi_unlink_batch()

• GDAL configuration: gdal_version, gdal_compute_version(), gdal_formats(), get_cache_used(), get_cache_max(), set_cache_max(), get_config_option(), set_config_option(), get_num_cpus(), get_usable_physical_ram(), has_spatialite(), http_enabled(), push_error_handler(), pop_error_handler(), dump_open_datasets()

• PROJ configuration: proj_version(), proj_search_paths(), proj_networking()

Additional functionality includes:

• RunningStats-class calculates mean and variance in one pass. The min, max, sum, and count are also tracked (efficient summary statistics on data streams).

• CmbTable-class implements a hash table for counting unique combinations of integer values.

• combine() overlays multiple rasters so that a unique ID is assigned to each unique combination of input values. Pixel counts for each unique combination are obtained, and combination IDs are optionally written to an output raster.

• calc() evaluates an R expression for each pixel in a raster layer or stack of layers. Individual pixel coordinates are available as variables in the R expression, as either x/y in the raster projected coordinate system or inverse projected longitude/latitude.

• plot_raster() displays raster data using base R graphics. Supports single-band grayscale, RGB, color tables and color map functions (e.g., color ramp).

Author

GDAL is by: Frank Warmerdam, Even Rouault and others
(see https://github.com/OSGeo/gdal/graphs/contributors)

R interface/additional functionality: Chris Toney

Maintainer: Chris Toney <chris.toney at usda.gov>

See also

GDAL Raster Data Model:
https://gdal.org/en/stable/user/raster_data_model.html

Raster driver descriptions:
https://gdal.org/en/stable/drivers/raster/index.html

Geotransform tutorial:
https://gdal.org/en/stable/tutorials/geotransforms_tut.html

GDAL Vector Data Model:
https://gdal.org/en/stable/user/vector_data_model.html

Vector driver descriptions:
https://gdal.org/en/stable/drivers/vector/index.html

GDAL Virtual File Systems:
https://gdal.org/en/stable/user/virtual_file_systems.html

Note

Documentation for the API bindings borrows heavily from the GDAL documentation, (c) 1998-2025, Frank Warmerdam, Even Rouault, and others, MIT license.

Sample datasets included with the package are used in examples throughout the documentation. The sample data sources include:

• LANDFIRE raster layers describing terrain, vegetation and wildland fuels (LF 2020 version)

• Landsat C2 Analysis Ready Data from USGS Earth Explorer

• Monitoring Trends in Burn Severity (MTBS) fire perimeters from 1984-2022

• NLCD Tree Canopy Cover produced by USDA Forest Service

• National Park Service Open Data vector layers for roads and points-of-interest

• Montana State Library boundary layer for Yellowstone National Park

Metadata for these sample datasets are in inst/extdata/metadata.zip and inst/extdata/ynp_features.zip.

system.file() is used in the examples to access the sample datasets. This enables the code to run regardless of where R is installed. Users will normally give file names as a regular full path or relative to the current working directory.

Temporary files are created in some examples which have cleanup code wrapped in dontshow{}. While the cleanup code is not shown in the documentation, note that this code runs by default if examples are run with example().