The distance map of a binarised raster contains the distance of each background cell to the nearest foreground cell.
rDistance(obj, method = "euclidean")
In contrast to
distance, the distance
values here do not warp around the boundaries of the map.
RasterLayer of the same dimension as
obj, where the
value of the background cells has been replaced with the distance to the
nearest foreground cell.
Meijster, A., Roerdink, J.B.T.M., Hesselink, W.H., 2000. A general algorithm for computing distance transforms in linear time, in: Goutsias, J., Vincent, L., Bloomberg, D.S. (Eds.), Mathematical Morphology and Its Applications to Image and Signal Processing. Springer, pp. 331–340.
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input <- rtData$continuous # the different distance metrics binarised <- rBinarise(input, thresh = 40) disEuc <- rDistance(binarised) disMan <- rDistance(binarised, method = "manhattan") disChb <- rDistance(binarised, method = "chessboard") distances <- raster::stack(binarised, disEuc, disMan, disChb) visualise(distances) # calculate distance from edge to patch interior inverted <- rPermute(binarised) visualise(rDistance(inverted))
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