Method for identifying points on the boundaries between regions (in most cases biases between countries)

1 | ```
findBoundaryLines(polygons, projOrig, projNew, regCode = "regCode")
``` |

`polygons` |
A |

`projOrig` |
The original projection of the boundaries |

`projNew` |
If a different projection is wanted for the output |

`regCode` |
the column name of regions in the data polygons |

This function finds the points defining the boundary between two polygons and
passes a `SpatialPointsDataFrame`

with these points back.
The result in mainly used by `findRegionalBias`

for estimation
of regional biases. The function is based on the boundary between the
polygons being defined by the same points.

A `SpatialPointsDataFrame`

with points defining the
boundaries between regions.

Jon Olav Skoien

Skoien, J. O., O. P. Baume, E. J. Pebesma, and G. B. M. Heuvelink. 2010. Identifying and removing heterogeneities between monitoring networks. Environmetrics 21(1), 66-84.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | ```
data(meuse)
observations = data.frame(x = meuse$x,y = meuse$y,value = log(meuse$zinc))
coordinates(observations) = ~x+y
pBoundaries = spsample(observations, 10, "regular", bb = bbox(observations) +
matrix(c(-400,-400,400,400),ncol=2),offset=c(0,0))
gridded(pBoundaries) = TRUE
cs = pBoundaries@grid@cellsize[1]/2
Srl = list()
nb = dim(coordinates(pBoundaries))[1]
for (i in 1:nb) {
pt1 = coordinates(pBoundaries)[i,]
x1 = pt1[1]-cs
x2 = pt1[1]+cs
y1 = pt1[2]-cs
y2 = pt1[2]+cs
boun = data.frame(x=c(x1,x2,x2,x1,x1),y=c(y1,y1,y2,y2,y1))
coordinates(boun) = ~x+y
boun = Polygon(boun)
Srl[[i]] = Polygons(list(boun),ID = as.character(i))
}
pBoundaries = SpatialPolygonsDataFrame(SpatialPolygons(Srl),
data = data.frame(ID=c(1:nb)))
observations$ID = over(observations, geometry(pBoundaries))
blines = findBoundaryLines(pBoundaries, regCode = "ID")
``` |

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