> On Mon, Aug 2, 2010 at 12:40 PM, Corrie Curtice <
cc157@...> wrote:
> > 2010/7/28 Damiano G. Preatoni <
prea@...>:
> >> In un messaggio del Wednesday 28 July 2010, Corrie Curtice ha scritto:
> >>> On Wed, Jul 28, 2010 at 2:35 AM, Anne Ghisla <
a.ghisla@...> wrote:
> >>> > On Tue, 2010-07-27 at 15:27 -0400, Corrie Curtice wrote:
> >>> >> Hello,
> >>> >>
> >>> >> I am trying to export the home range for a single individual animal.
> >>> >> I'm getting the error "Error in re[[i]] : subscript out of bounds"
> >>> >> -- I looked on the archive and found my own posting of this
> >>> >> question for the 100% isopleth. :) So now I'm wondering, why does
> >>> >> the error occur at lower isopleth levels? Ideally I would like the
> >>> >> 95% KHRE to show the "home range" of each animal, and this works
> >>> >> with all other individuals. The answer to my last posting noted
> >>> >> that the isopleth went beyond the grid limits. I'm not passing in
> >>> >> an underlying grid. Here's my call:
> >>> >>
> >>> >> ud <- kernelUD(xy, grid=100, h="href")
> >>> >> kvtmp <- getverticeshr(ud, lev = 95)
> >>> >>
> >>> >> Levels up to 85 work fine. Is there anything I can do to fix this,
> >>> >> if not what is the proper way to report the result for this animal?
> >>> >> If you need more code or output I can send.
> >>> >
> >>> > Hi Corrie,
> >>> >
> >>> > it sounds like the issue reported here:
> >>> >
> >>> >
https://trac.faunalia.it/animove/ticket/13> >>> >
> >>> > does your dataset show anisotropy? The one attached to the ticket is
> >>> > a narrow cloud of points along a horizontal line. The default grid
> >>> > created by kernelUD is likely not able to encompass the whole UD. If
> >>> > the case, I would try creating a wider grid and providing it to
> >>> > kernelUD.
> >>> >
> >>> > hope this helps!
> >>>
> >>> Yes, that's exactly it. I tried increasing the value passed into the
> >>> grid parameter -- is this right? Is there some way to determine what
> >>> the correct value would be?
> >>
> >> There is no "correct" value for the grid parameter.
> >> It it a known "feature" of adehabitat.
> >>
> >> That is, passing "grid=<some integer value>" means that kernel
> >> calculations (see e.g. Worton classical text) start with superimposing
> >> your point locations a mesh with <integer value> x <integer value>
> >> _cells_. Worton's default is 40x40.
> >>
> >> Problem is that is more meaningful having the possibility to supply the
> >> _cell size_ insteda of the _number of cells_.
> >>
> >> This means that if your points cloud covers a _wide_ extent, say, half a
> >> state, you will have in your case a 100x100 cells mesh, and a single
> >> cell side will be some tenths of kilometers!
> >>
> >> To overcome this problem, one should use "grid=<a kasc object>" (look
> >> into kernelUD source...).
> >>
> >> I normally do like this:
> >> - using my favorite GIS package, I create a raster with the cell size I
> >> want, making it so that covers my study area. This way I'll have for
> >> instance a raster with 100 m cells, with a size of such and such rows
> >> and columns (I say 'such and such' since we're not interested in how
> >> many squares we have, but in how long is a square side!).
> >> - I export that raster in ASCII GRID format.
> >> - back into R I use read.asc function and create a kasc object that then
> >> I will use as my "reference grid" in home range calculations, like
> >> this:
> >>
> >> my.reference.grid <- read.asc('refgrid.asc')
> >> ud <- kernelUD(xy, grid=my.reference.grid, h="href")
> >
> > Thanks Damiano, this is helpful information. I have a follow up question.
> >
> > It sounds like from what you say, that the smaller cell size is
> > better. ie: 100m vs 1000m or greater. I've read quite a bit of
> > background lit, but until I try this on my own I don't fully
> > understand all the implications. I am not able to find much that
> > discusses the impact of cell size during kernel calculation. More
> > focus is on the smoothing parameter.
> >
> > I created a grid of 100m cells, and re-ran the kernelUD for one set of
> > animals in my study (at one island). The UDs in this home range are a
> > bit smaller and more detailed than the ones created with 100x100 grid,
> > pretty close but I do like it a little better.
> >
> > So, is there a process to decide on the best cell size, related to the
> > data? Would I be safe to pick 100m for each of my sites and
> > individuals? These are marine mammals that range over wide areas,
> > some as far as almost 300km, but mostly w/in 100km.
>
> I retract that comment: the UDs created are exactly the same -- I was
> looking at a wrong image when comparing the first time, apologies.
> Thanks for the guidance.
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