## rasterTools

Obtain and Process Earth Observation Data

The rasterTools package provides a toolkit to obtain and process spatial (earth observation) data in a transparent and reproducible manner.

## Getting Started

1. Install the development version from github via:

devtools::install_github("EhrmannS/rasterTools")
2. Read a brief introduction to understand the philosophy of rasterTools:

?rasterTools-package
3. The vignettes given an in detail Introduction and explain what the logic behind landscape metrics is.

## Example workflow

1. (Down)load a range of gridded datasets:

myDatasets <- list(list(operator = "oGFC", years = 2006)),
list(operator = "oMODIS", product = "mod17a3",
period = 2006, layer = 2),
...)
myData <- obtain(data = myDatasets, mask = aMask)
2. Determine forest patches in a raster with continuous integer values of tree-cover:

get_patches <- list(list(operator = "rBinarise", thresh = 30),
list(operator = "rPatches"))
myInput <- rtData$continuous myPatches <- modify(input = myInput, by = get_patches, sequential = TRUE) visualise(raster::stack(myInput, myPatches)) 1. Compute the Class proportional area in a raster with categorial values: myInput <- rtData$categorial
myMetric <- list(a_l = list(operator = "mArea", scale = "landscape"),
a_c = list(operator = "mArea", scale = "class"),
mCPA = "a_c / a_l * 100")
measure(input = myInput, with = myMetric)
2. Share your algorithms (or a gist thereof) on twitter with #rtAlgos.

## Planned for future versions

• Support of the Sentinel, Landsat and Lidar datasets.

• Support of various “national forest inventory” datasets (Germany, France, Italy, Spain, yours?)

• rTilify() to segregate a gidded dataset into another tiling, for instance to align datasets to each other or produce a hexagonal tiling of a rectangluarly tiled dataset.

• You are encouraged to participate by writing for instance an obtain operator for your favourite dataset.

## Acknowledgements

I am grateful for financial support from the PROFOUND Cost-action, which gave me the opportunity to work in a concentrated effort a large part of the functionality. This package has been developed in support of the FunBo Project, which was made possible by the Grünewald-Zuberbier Scholarship handed out by the University of Freiburg.

Thanks are due to Prof. Arne Pommerening who was a great source of inspiration for what rasterTools is now.