In hypertidy/rasterio.py: An R Interface to rasterio

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

rasterio.py

The goal of rasterio.py is to provide an R interface to rasterio.

rasterio is a Python package that provides low-level facilities to the GDAL, much like the R rgdal did in the past. The Python bindings have always been closer and more complete to the spirit of the GDAL library itself than R, but rasterio itself is a modernization of the original Python support for GDAL.

R does not have a comprehensive interface to the GDAL C++ library yet, so this package provides a showcase of what is possible. The facilities via Python are fine! The only real disadvantage is the dependency on Python, there's no obvious performance reason to avoid rasterio however.

Installation

You can install the development version of rasterio.py like so:

# FILL THIS IN! HOW CAN PEOPLE INSTALL YOUR DEV PACKAGE?

Example

This is a basic example which shows you how to solve a common problem:

library(rasterio.py)
## basic example code
file <- rgba_tif()  ## just the path to the RGBA.byte.tif of rasterio canon
dataset <- open.py(file)

dataset$bounds
dataset$transform

rasterio.py has some R helper functions for these Python reticulate objects.

plot, extent, more to come ...

WIP

plot(dataset)

extent.py(dataset)

(warped <- warp.py(dataset$files[1], extent = c(-1, 1, -1, 1) * 1e5, dimension = c(512, 768), projection = "+proj=aeqd +lon_0=-77.6 +lat_0=24.5", resample = "cubic"))

plot(warped)

We can of course read from the COG!! (but, overview handling isn't great yet so we're keeping examples close)

gebco <- "/vsicurl/https://public.services.aad.gov.au/datasets/science/GEBCO_2019_GEOTIFF/GEBCO_2019.tif"

dem <- open.py(gebco)
plot(dem)

dem <- warp.py(gebco, extent = c(130, 170, -65, -35), dimension = c(720, 360), projection = "OGC:CRS84")
plot(dem)