Package index • vrtility

VRT Core Functions

Core functions for Virtual Raster management

vrt_collect() print(<vrt_collection>) c(<vrt_block>) c(<vrt_collection>): Construct the base VRT object for composing VRT pipelines.

vrt_warp(): Construct A warped VRT or warped VRT collection.

vrt_stack() print(<vrt_stack>): Stack VRT files from a vrt_collection object

vrt_compute(): Generate a composite raster from (virtual) raster sources.

VRT Pixel Functions

Functions for pixel-wise operations on VRT rasters

vrt_set_gdal_pixelfun(): Set built-in GDAL pixel functions of a VRT stack object

vrt_set_py_pixelfun() median_numpy() mean_numpy() geomean_numpy() quantile_numpy() mean_db_numpy(): Set the pixel function of a VRT stack object

vrt_derived_block(): Create vrt blocks with derived bands.

Image Masking

Functions for creating and applying image masks

vrt_set_maskfun() set_mask_numpy() build_intmask() build_bitmask(): Set mask band of a VRT collection

vrt_create_mask() create_omnicloudmask(): Create a new mask for a vrt object This function allows you to create a mask for a VRT object based on specified input bands and a mask function.

VRT helpers

Helper functions for VRT objects

vrt_set_band_names(): set the band names for a vrt_x object

vrt_save(): Save a vrt_block object to disk

vrt_add_empty_band(): Add an empty band to a VRT_x object

vrt_move_band(): Add an empty band to a VRT_x object

vrt_set_scale(): set the scale values for a VRT_x object

vrt_set_nodata(): Set NoData Value for VRT

vrt_xml_schema vrt_schema(): The official GDAL VRT XML schema A copy of the official VRT schema for vritility VRT validation.

multi-band reduction funcions

Functions to create composites using multi-band algorithms

multiband_reduce() geomedian() medoid() quantoid() geomedoid(): Image composite reductions that require all bands.

single-band many-to-many functions

Functions designed to work with time-series, namely applying outlier filtering.

singleband_m2m() hampel_filter(): Image processing along a time series.

GDAL Configuration

GDAL configuration and setup functions

gdal_config_opts() gdal_creation_options() gdalwarp_options() set_gdal_config() set_gdal_cache_max() gdal_raster_drivers() check_muparser(): Create and set GDAL configuration options.

Python Integration

Python environment and computation environment

vrtility_py_require() set_py_env_vals() compute_with_py_env(): Setup the vrtility Python environment

STAC Functions

STAC query and planetary computer functions

stac_query() sentinel2_stac_query() hls_stac_query() sentinel1_stac_query() stac_cloud_filter() stac_orbit_filter() stac_coverage_filter() sign_mpc_items() stac_drop_duplicates(): Query a STAC source

Raster visualisation

plotting functions for raster files and vrt_x objects

plot(<Rcpp_GDALRaster>) plot_raster_src() plot(<vrt_block>) plot(<vrt_stack>) plot(<vrt_stack_warped>) plot(<vrt_collection>): plot a raster file or vrt_x object

Cache management

Helper functions for managing / altering vrtility cache settings

vrt_cache_set() vrt_cache_destroy(): Set the VRT cache directory

parallel processing helpers

Helper functions for parallel processing

n_daemons(): Mirai Daemon Management

Spatial helper functions

Helper functions for spatial operations

bbox_to_projected() to_wkt(): Project a lat/long bounding box to a generic projected coordinate system

gdalraster helpers

Helper functions for GDALRasterDataset objects

r_to_MEM(): Create an in-memory GDAL raster dataset from R data