Dear Loic,

Thank you for your reply!

Re. aggregation, I agree - I will use either mean or median.

gcp_grid are points as below

structure(list(longitude = c(-179L, -178L, -177L, -177L, -177L,
-176L), latitude = c(-15L, -15L, -14L, 51L, 52L, -22L)), .Names =
c("longitude",
"latitude"), row.names = c("1", "2", "3", "4", "5", "6"), class =
"data.frame")

Thank you for your suggestion on the additional options, I will look them
up. Would you say I am on the right path after the changes? Thanks again!

Sincerely,

Milu

On Fri, Jan 13, 2017 at 3:35 PM, Loïc Dutrieux <loic.dutri...@conabio.gob.mx
> wrote:

>
>
> On 13/01/2017 10:59, Miluji Sb wrote:
> > Thank you for your reply. This is what I did:
> >
> > ###
> > library(data.table)
> > library(raster)
> > library(rgdal)
> > library(foreign)
> >
> > elevation_world <- getData('worldclim', var='alt', res=2.5)
> >
> > # Aggregate Elevation to 1 degree
> > elevation_world_1deg <- aggregate(elevation_world, fact = 24, fun = sum)
>
> Aggregating with fun=sum is a bit strange for elevation. mean or median
> would certainly be a better choice.
>
> >
> > # Extract by lon lat (1° x 1° - gcp_grid)
> > elevation <- cbind(gcp_grid, alt = extract(elevation_world_1deg,
> gcp_grid))
>
> gcp_grid are points or polygons? If they are polygons, there's no need
> for the aggregation step above. Also have a look at df = TRUE, which
> returns a dataframe, and sp=TRUE, which returns a Spatial*DataFrame with
> extracted values cbinded to the attributes of the original
> Spatial*DataFrame. (both are arguments of raster::extract)
>
> Cheers,
> Loïc
>
> >
> > elevation <- as.data.frame(elevation)
> > ###
> >
> > Is this correct? Thanks again!
> >
> > Sincerely,
> >
> > Milu
> >
> > On Fri, Jan 13, 2017 at 3:11 AM, Bacou, Melanie <m...@mbacou.com> wrote:
> >
> >> R raster::getData("SRTM", ...) will return elevation rasters at 90m
> >> resolution.
> >> See:
> >> https://www.rdocumentation.org/packages/raster/versions/2.5-
> >> 8/topics/getData
> >> http://www.cgiar-csi.org/data/srtm-90m-digital-elevation-database-v4-1
> >>
> >> --Mel.
> >>
> >>
> >> On 1/11/2017 6:26 AM, Miluji Sb wrote:
> >>
> >>> Dear Michael,
> >>>
> >>> Thank you for your reply and the suggestions.
> >>>
> >>> Ideally, I would like a raster from which I can extract elevation at
> 1° x
> >>> 1° resolution. I do not have much experience with working with DEM but
> >>> have
> >>> work with data such as GPW.
> >>>
> >>> I will definitely look at the datasets. Could you kindly suggest one
> that
> >>> I
> >>> could convert to raster and extract? Hope that's not a silly question.
> >>>
> >>> Sincerely,
> >>>
> >>> Milu
> >>>
> >>> On Wed, Jan 11, 2017 at 1:51 AM, Michael Sumner <mdsum...@gmail.com>
> >>> wrote:
> >>>
> >>> Passed through? Maybe you want ?raster::extract
> >>>>
> >>>> There are a few versions of global elevation on CRAN, necessarily at
> low
> >>>> resolution but no overall summary afaik (someone should do this :).
> >>>>
> >>>> This is one: https://cloud.r-project.org/
> web/packages/GEOmap/index.html
> >>>>
> >>>> If you have the stomach for development versions of packages see
> elevatr:
> >>>> https://github.com/jhollist/elevatr
> >>>>
> >>>> I tend to have the high-resolution files at hand because we use them
> >>>> constantly, the main ones are Gebco14/Gebco08 and Etopo1/Etopo2 (from
> >>>> Smith-Sandwell).
> >>>>
> >>>> There's a reasonable overview here, you probably should find a
> specific
> >>>> data set that is at the resolution you are after already, and you can
> >>>> cite
> >>>> its derivation for your work:
> >>>>
> >>>> http://vterrain.org/Elevation/global.html
> >>>>
> >>>> Cheers, Mike.
> >>>>
> >>>> On Wed, 11 Jan 2017 at 10:20 Miluji Sb <miluj...@gmail.com> wrote:
> >>>>
> >>>> Dear all.
> >>>>>
> >>>>> Is there a way to download global elevation data at the 1° x 1°
> >>>>> resolution
> >>>>> in R using a given set of coordinates?
> >>>>>
> >>>>> I know about the getData() function but can many coordinates be
> passed
> >>>>> through this? Thanks!
> >>>>>
> >>>>> Sincerely,
> >>>>>
> >>>>> Milu
> >>>>>
> >>>>>          [[alternative HTML version deleted]]
> >>>>>
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> >>>>>
> >>>>>
> >>>>> University of Tasmania Electronic Communications Policy (December,
> >>>>> 2014).
> >>>>> This email is confidential, and is for the intended recipient only.
> >>>>> Access, disclosure, copying, distribution, or reliance on any of it
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> >>>>> .
> >>>>>
> >>>>> --
> >>>> Dr. Michael Sumner
> >>>> Software and Database Engineer
> >>>> Australian Antarctic Division
> >>>> 203 Channel Highway
> >>>> Kingston Tasmania 7050 Australia
> >>>>
> >>>>
> >>>>         [[alternative HTML version deleted]]
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