PixelCt | R Documentation |

In order to produce reliable results, the cross-covariance approach
implemented in `DispField`

. `DispFieldST`

, and
`DispFieldSTall`

needs a certain minimum number of non-zero or
non-NA valued pixels in pairs of images or pairs of arrays derived from a
raster stack that it uses to compute cross-covariance. The user may define a
threshold such as ten percent of the pixels within each sub-grid. This
function allows the user to assess whether the minimum threshold number of
non-zero pixels per sub-grid are surpassed by returning the number of
non-zero pixels within each sub-grid over all of the time instances in the
user-supplied raster stack. The user may choose to disregard or mistrust
displacement or velocity estimates derived from sub-grids with insufficient
numbers of non-zero pixels. This function is designed to be called before or
after one of the functions referenced above in order to enable the user to
quantify their confidence in displacement or velocity estimates.

PixelCt(inputstack1, factv1, facth1)

`inputstack1` |
a raster stack with each raster layer representing an instance of time. The raster stack should be organized such that the first raster in the stack is the first observed spatial dataset and time progresses forward with the third dimension index of the raster stack. The raster stack should contain only numeric values. Any NA value will be converted to a zero |

`factv1` |
an odd integer for the vertical dimension of subgrids |

`facth1` |
an odd integer for the horizontal dimension of subgrids |

A data frame is returned with the following column names: rowcent, colcent, frowmin, frowmax, fcolmin, fcolmax, and PixelCt. The rowcent and colcent column names are the row and column indices for the center of each sub-grid; frowmin and frowmax are the sub-grid minimum and maximum row indices; fcolmin and fcolmax are the sub-grid minimum and maximum column indices; pixelct is the count of non-zero pixels in the sub-grid over the entire time period covered by the input raster stack.

# below the example in the DispField function documentation is reproduced (Mat1 <- matrix(rep(c(1:5, 0, 0, 0, 0), 9), nrow = 9, byrow = TRUE)) (Mat2 <- matrix(rep(c(0, 1:5, 0, 0, 0), 9), nrow = 9, byrow = TRUE)) # Note that rasterizing a matrix causes it to be rotated 90 degrees. # Therefore, any shift in the x direction is in fact now a shift in the y direction rast1 <- terra::rast(Mat1) terra::plot(rast1) rast2 <- terra::rast(Mat2) terra::plot(rast2) (Confdf1 <- PixelCt(c(rast1, rast2), factv1 = 9, facth1 = 9)) # This should return a pixel count of 54: This is the number # of pixels that were occupied in either the first or second # time instance.

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