[R-sig-Geo] Antw: Re: Re: Re: Creating a spatialPolygonsDataFrame from a data frame
Matteo Mattiuzzi
matteo.mattiuzzi at boku.ac.at
Sun Oct 7 21:02:52 CEST 2012
getTile uses this information. But If you are looking for a modification (ie a simpler way to define point location) I could add it.
>>> steven mosher 07.10.12 20.44 Uhr >>>
ok. I should be able to work with that.
my approach with the G-ring data was giving odd results anyways.
On Sun, Oct 7, 2012 at 10:53 AM, Matteo Mattiuzzi <
matteo.mattiuzzi at boku.ac.at> wrote:
> This is what I can serve:
>
>
> getTile(extent="path/to/your/file.shp")$tile # poly
> getTile(extent="path/to/your/raster.file")$tile # rasterfile
> getTile(extent=extent("raster.file"))$tile # raster extent
> getTile(extent="austria")$tile # charackter name
> getTile(extent=list(xmin,xmax,ymin,ymax))$tile #
>
>
>
> interactive it is only if you don't give any arguments
> I think the only thing what is missing is sp:::bbox (I use
> raster:::extent) but I coud add it very easily. And the point (I use
> list(xmin,xmax...))
>
> >>> steven mosher 07.10.12 19.37 Uhr >>>
>
>
> I looked at that code. I didn't want to do this via interactive map. and I
> just wanted a very simple super simple api. getVH(lonlat) or a case that
> accepts poly or bbox as input.
>
> On Sun, Oct 7, 2012 at 10:23 AM, Matteo Mattiuzzi <
> matteo.mattiuzzi at boku.ac.at> wrote:
>
> > If MODIS tiles are your aim why don't you use?
> >
> >
> > MODIS:::getTile()
> >
> >
> >
> > >>> steven mosher 07.10.12 19.11 Uhr >>>
> > Well I'm just puttering around and got kinda tired of pulling up Google
> > Earth everytime I wanted to locate a MODIS Tile from lat/lon. so I
> found
> > the the following
> >
> > gring <-"
> > http://landweb.nascom.nasa.gov/developers/sn_tiles/sn_gring_10deg.txt"
> >
> >
> >
> > GRING <- read.table(gring, skip = 7, stringsAsFactors =FALSE,
> nrows=648,
> > na.strings=c("-999.0000","-99.0000"))
> >
> > colnames(GRING)<-c("v","h","ll_lon","ll_lat",
> > "ul_lon","ul_lat","ur_lon","ur_lat",
> > "lr_lon","lr_lat")
> >
> >
> >
> >
> > On Sun, Oct 7, 2012 at 9:51 AM, Matteo Mattiuzzi <
> > matteo.mattiuzzi at boku.ac.at> wrote:
> >
> > > Hi Steve, what about this?
> > >
> > >
> > > DF <- structure(list(v = c(4L, 4L, 4L, 4L, 4L, 4L, 4L), h = 8:14,
> ll_lon
> > =
> > > c(-131.0149,
> > > -117.7464, -104.5202, -91.3388, -78.2083, -65.15, -52.1199),
> > > ll_lat = c(39.7081, 39.7342, 39.7557, 39.7728, 39.7858, 39.7937,
> > > 39.7994), ul_lon = c(-156.8405, -140.7952, -124.8854, -109.0855,
> > > -93.3822, -77.7862, -62.229), ul_lat = c(49.8983, 49.9394,
> > > 49.9677, 49.9863, 49.9972, 50, 50), ur_lon = c(-140.2398,
> > > -124.6153, -109.0021, -93.3968, -77.7506, -62.1191, -46.5357
> > > ), ur_lat = c(50.1258, 50.1159, 50.1047, 50.0921, 50.0754,
> > > 50.0582, 50.0429), lr_lon = c(-117.2848, -104.2354, -91.191,
> > > -78.1497, -65.0781, -52.0094, -38.9707), lr_lat = c(39.8699,
> > > 39.8624, 39.8554, 39.8489, 39.8411, 39.8337, 39.828)), .Names =
> c("v",
> > > "h", "ll_lon", "ll_lat", "ul_lon", "ul_lat", "ur_lon", "ur_lat",
> > > "lr_lon", "lr_lat"), row.names = 153:159, class = "data.frame")
> > >
> > >
> > >
> > >
> > > SPDF <- list()
> > > id <- matrix(NA,nrow(DF),ncol=2)
> > > colnames(id)<- c("h","v")
> > > for (u in 1:nrow(DF))
> > > {
> > > SPDF[[u]] <- Polygons(list(Polygon(cbind(
> > > c(DF$ll_lon[u], DF$ul_lon[u], DF$ur_lon[u], DF$lr_lon[u],
> DF$ll_lon[u]),
> > > c(DF$ll_lat[u], DF$ul_lat[u], DF$ur_lat[u], DF$lr_lat[u],
> DF$ll_lat[u])),
> > > hole = FALSE)),u)
> > > id[u,] <- c(DF$h[u], DF$v[u]) # probably h/v information can be taken
> > > direcly from DF
> > > }
> > > SPDF <-
> > SpatialPolygons(SPDF,1:length(SPDF),proj4string=CRS("+proj=longlat
> > > +ellps=WGS84 +datum=WGS84 +no_defs"))
> > > SPDF <- SpatialPolygonsDataFrame(SPDF,
> > > as.data.frame(id),match.ID=FALSE)
> > > plot(SPDF,col="green")
> > >
> > >
> > >
> > >
> > > >>> steven mosher 07.10.12 8.18 Uhr >>>
> > > Hi,
> > >
> > > I have a dataframe that has a few hundred rows like this.
> > >
> > > DF <- structure(list(v = c(4L, 4L, 4L, 4L, 4L, 4L, 4L), h = 8:14,
> ll_lon
> > =
> > > c(-131.0149,
> > > -117.7464, -104.5202, -91.3388, -78.2083, -65.15, -52.1199),
> > > ll_lat = c(39.7081, 39.7342, 39.7557, 39.7728, 39.7858, 39.7937,
> > > 39.7994), ul_lon = c(-156.8405, -140.7952, -124.8854, -109.0855,
> > > -93.3822, -77.7862, -62.229), ul_lat = c(49.8983, 49.9394,
> > > 49.9677, 49.9863, 49.9972, 50, 50), ur_lon = c(-140.2398,
> > > -124.6153, -109.0021, -93.3968, -77.7506, -62.1191, -46.5357
> > > ), ur_lat = c(50.1258, 50.1159, 50.1047, 50.0921, 50.0754,
> > > 50.0582, 50.0429), lr_lon = c(-117.2848, -104.2354, -91.191,
> > > -78.1497, -65.0781, -52.0094, -38.9707), lr_lat = c(39.8699,
> > > 39.8624, 39.8554, 39.8489, 39.8411, 39.8337, 39.828)), .Names =
> > c("v",
> > > "h", "ll_lon", "ll_lat", "ul_lon", "ul_lat", "ur_lon", "ur_lat",
> > > "lr_lon", "lr_lat"), row.names = 153:159, class = "data.frame")
> > >
> > >
> > > The columns are v and h, two attributes, and then 4 points in lat
> and
> > > lon ll_lon is lower left lon, lr_lon is lower right,
> > > ul_lon is upper left and ur_lon is upper right.
> > >
> > > What I want to do is create a spatialPolygonsDataFrame from this data.
> > > As best as I can figure I have to take the lon/lat coordinates and put
> > > them in to a matrix format, replicate the first point to close
> > > the ring and create a Polygon, and then Create a Polygons() object with
> > an
> > > ID and then a SpatialPolygon, and then a
> > > SpatialPolygonDataFrame from a list of the spatial polygons.
> > >
> > > What I'm struggling with is how to do this for the several hundred rows
> > > that I have.
> > >
> > > Steve
> > >
> > > [[alternative HTML version deleted]]
> > >
> > > _______________________________________________
> > > R-sig-Geo mailing list
> > > R-sig-Geo at r-project.org
> > > https://stat.ethz.ch/mailman/listinfo/r-sig-geo
> > >
> > >
> > >
> >
> >
> >
>
>
>
More information about the R-sig-Geo
mailing list