This is caused by the plotting function which only plots a sample of the pixels for speed reasons. You can tweak it.

Here's a reproducible example taken from one feature from your shape:
These coordinates are part of one feature in your data:

```
xy = structure(c(417476.8675, 417468.8832, 417473.037, 417458.7495, 
417352.3868, 417328.5742, 417318.52, 417303.7033, 417293.8735, 
5887737.1296, 5887834.9375, 5887938.579, 5888021.6583, 5888042.825, 
5888022.7166, 5887966.6249, 5887940.1665, 5887907.6158), .Dim = c(9L, 
2L), .Dimnames = list(NULL, c("x", "y")))
```

and we make a `SpatialLines` object out of it:

```
ltest = SpatialLines(list(Lines(list(Line(xy)),ID=1)))
```

we'll use a raster with a much larger extent:

```
e = extent(c(xmin=414500,xmax=424500,ymin=5882000,ymax=5890000))
```

Now try and rasterize over a fine grid on that raster:

```
r5 <- raster(ncol=4000, nrow=4000, extent(e))
rtest = rasterize(ltest,r5)
plot(ltest)
plot(rtest,add=TRUE)
```

[![enter image description here][1]][1]

That only shows a few pixels. But...

    > sum(rtest[],na.rm=TRUE)
    [1] 299

tells me there's 299 pixels. Change the `maxpixels` value to plot and:

    > plot(ltest)
    > plot(rtest,add=TRUE,maxpixels=ncell(rtest))

it looks fine:

[![enter image description here][2]][2]

Note the pixels seem much smaller than in the first plot, because I think when it subsamples them it also rescales them in size so they are visible in a full plot - that makes them way too big in a zoomed plot.

Any analysis you do with this raster will work fine, its only plotting that's affected and then you can fix that with `maxpixels`. Its not a bug despite what my earlier version may have said!


  [1]: https://i.sstatic.net/cMggC.png
  [2]: https://i.sstatic.net/xJp3b.png