In EhrmannS/rasterTools: Obtain and process earth observation data

knitr::opts_chunk$set(echo = TRUE)

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.

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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.

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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))

3) 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)

4) Share your algorithms (or a gist thereof) on twitter with #rtAlgos.

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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.

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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.

EhrmannS/rasterTools documentation built on Sept. 4, 2019, 10:34 a.m.