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.
Install the development version from github via:
Read a brief introduction to understand the philosophy of
(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)
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$continuous myPatches <- modify(input = myInput, by = get_patches, sequential = TRUE) visualise(raster::stack(myInput, myPatches))
Compute the Class proportional area in a raster with categorial values:
myInput <- rtData$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)
Share your algorithms (or a gist thereof) on twitter with #rtAlgos.
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.
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.