[R-sig-Geo] Guidance on adehabitat usage
Jefferson Ferreira Ferreira
jecogeo at gmail.com
Wed Feb 26 14:43:20 CET 2014
Dear forum members
I had successful use adehabitatHR R package to estimate home ranges for
jaguar based on collar data. Now I'm trying to analyse relocations with
adehabitatLT package following the vignette (
http://cran.r-project.org/web/packages/adehabitatLT/vignettes/adehabitatLT.pdf).
But some doubts emerged and if some of you could clarify me I'll be pleased
to hear your suggestions.
My collar data have +/- 19% of missing data due to problems related to
receiving GPS signal from collar. So, I've filtered the data:
#re-subseting to exclude rows with no coordinates
coto_nonas2 <- subset(coto, coto$GPS_Latitude != 'NA')
(1) In your opinion, is this procedure correct?
Well, after this i've execute
#Placing the missing values in the trajectory
# The relocations have been collected daily, but there are many days during
which
# this relocation was not possible (storm, lack of field workers, etc.).
# We need to add missing values to define a regular trajectory.
# We have to define a reference date that will be used to check that each
date in
# the object of class ltraj is separated from this reference by an integer
multiple
# of the theoretical dt (here, one day), and place the missing values at
the times
# when relocations should theoretically have been collected.
refdata <- strptime('2013-02-13 00:00:00', '%Y-%m-%d %H:%M:%S')
# function setNA to place the missing values with theoretical collects
every 6 hours
coto_moves2 <- setNA(coto_moves, refdata, 6, units = 'hour')
# Even when filling the gaps with NAs, the trajectory is still not regular.
# The function sett0 can be used to 'round' the timing of the coordinates.
coto_moves3 <- sett0(coto_moves2, refdata, 6, units = "hour")
And from then, I filled with doubts.
My wawotest returned any correlation among the variables.
dx dy dist
a 24.6905441 42.29083967 24.6541496
ea -1.0000000 -1.00000000 -1.0000000
va 403.9675822 405.47166447 409.2888978
za 1.2782036 2.14988760 1.2680683
p 0.1005888 0.01578205 0.1023868
(2) should I discretize the the data in space? Or in time?
As say in other message in r-sig-geo forum, I'm a begginer and
unfortunately working alone. Could you please provide me some guidance with
this?
Any suggestions will be appreciated.
Follows attached a snippet of my data and my script if it can be useful.
Best regards
--
*Jefferson Ferreira-Ferreira*
Geógrafo - GEOPROCESSAMENTO IDSM | Coordenadoria de TI
Jefferson.ferreira at mamiraua.org.br
*Instituto de Desenvolvimento Sustentável Mamirauá*
Ministério da Ciência, Tecnologia e Inovação
Telefone: +55 97 3343-9710
*Google Maps* - Mapas deste e-mail:
Exibir mapa ampliado<https://maps.google.com.br/maps?q=-3.355557,-64.731151&ll=-3.355471,-64.731145&spn=0.004632,0.006968&num=1&t=h&z=18>
*Contatos particulares:*
*(55) 9615-0100 <%2855%29%209615-0100>*
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <https://stat.ethz.ch/pipermail/r-sig-geo/attachments/20140226/d0746c03/attachment.html>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: jaguar.zip
Type: application/zip
Size: 18235 bytes
Desc: not available
URL: <https://stat.ethz.ch/pipermail/r-sig-geo/attachments/20140226/d0746c03/attachment.zip>
More information about the R-sig-Geo
mailing list