A lightweight GDAL API package for R.
Provides low-level access to 'GDAL' functionality for R packages. The aim is to minimize the level of interpretation put on the 'GDAL' facilities, to enable direct use of it for a variety of purposes. 'GDAL' is the 'Geospatial Data Abstraction Library' a translator for raster and vector geospatial data formats that presents a single raster abstract data model and single vector abstract data model to the calling application for all supported formats http://gdal.org/.
Lightweight means we access parts of the GDAL API as near as possible to their native usage. GDAL is not a lightweight library, but provide a very nice abstraction over format details for a very large number of different formats.
Functions for raster and vector sources are included.
#'
vapour_all_drivers |
list of all available drivers, with type and features |
vapour_gdal_version |
report version of GDAL in use |
vapour_raster_gcp |
return internal ground control points, if present |
vapour_raster_info |
structural metadata of a source |
vapour_read_raster |
read data direct from a window of a raster band source |
vapour_sds_names |
list individual raster sources in a source containing subdatasets |
vapour_driver |
report name of the driver used for a given source |
vapour_geom_summary |
report simple properties of each feature geometry |
vapour_layer_names |
list names of vector layers in a data source |
vapour_read_names |
read the 'names' of features in a layer, the 'FID' |
vapour_read_attributes |
read attributes of features in a layer, the columnar data associated with each geometry |
vapour_read_extent |
read the extent, or bounding box, of geometries in a layer |
vapour_read_geometry |
read geometry in binary (blob, WKB) form |
vapour_read_geometry_text |
read geometry in text form, various formats |
vapour_report_attributes |
report internal type of each attribute by name |
As far as possible vapour aims to minimize the level of interpretation provided for the functions, so that developers can choose how things are implemented. Functions return raw lists or vectors rather than data frames or classed types.