|
|
|
|
Dear R-Sig-Geo Members,
I've like to extract xy coordinates from raster of 24 neigborhood
cells that surround the 4 given points (pts_s) pixels and for this I used:
#Packages
require(raster)
require(sp)
## Create a raster
r <- raster(nc=30, nr=30)
r <- setValues(r, round(runif(ncell(r))* 255))
plot(r)
##Given interesting points coordinates
xd <- c(-24.99270,45.12069,99.40321,73.64419)
yd <- c(-45.435267,-88.369745,-7.086949,44.174530)
pts <- data.frame(xd,yd)
pts_s<- SpatialPoints(pts)
points(pts_s, col="red", pch=16)
## Find pixels center of each point (My idea is not to use the original
point coordinates, but coordinates of the center of interesting pixel).
N_cells <- cellFromXY(r, pts_s)
# Extract xy coordinates from raster of 24 neighborhood cells given
pixel number N_cells
e<-adjacent(r, N_cells , directions='bishop', id=TRUE)
coordinates(land_mask)[e[,1],] ## Doesn't return 24 neighborhood by
N_cells object
ng_coords<-coordinates(land_mask)[e[,1],]
#
#Visualization
plot(r)
points(pts_s, col="red", pch=16)
points(ng_coords, col="black", pch=16)
##
But I don't have success because the ng_coords object is not a 24
neighborhood cells of each point that I search. There are solution for this?
Thanks in advance,
Alexandre
--
======================================================================
Alexandre dos Santos
Proteção Florestal
IFMT - Instituto Federal de Educação, Ciência e Tecnologia de Mato Grosso
Campus Cáceres
Caixa Postal 244
Avenida dos Ramires, s/n
Bairro: Distrito Industrial
Cáceres - MT CEP: 78.200-000
Fone: (+55) 65 99686-6970 (VIVO) (+55) 65 3221-2674 (FIXO)
[hidden email]
Lattes: http://lattes.cnpq.br/1360403201088680OrcID: orcid.org/0000-0001-8232-6722
Researchgate: www.researchgate.net/profile/Alexandre_Santos10
LinkedIn: br.linkedin.com/in/alexandre-dos-santos-87961635
Mendeley:www.mendeley.com/profiles/alexandre-dos-santos6/
_______________________________________________
R-sig-Geo mailing list
[hidden email]
https://stat.ethz.ch/mailman/listinfo/r-sig-geo
|
|
|
Hi,
I'm not sure why you expect 24 points - you have 4 locations and for each you want the 4 bishop's directions - so, I think at most you should expect 16 points. See http://www.lpc.uottawa.ca/publications/moransi/moran.htm < http://www.lpc.uottawa.ca/publications/moransi/moran.htm> for where I expect 4 points for bishop's for each input location; perhaps you have a different idea of bishop's direction?
Your second point [45.12069, -88.369745] is on to the southern edge of the raster - so it can't find points southward - only the 2 northward.
Finally, it may not make any difference at all, but your pts_s has no coordinate reference. Below I show where I assign the same projection as your raster. I also don't have 'land_mask' so I reused 'r' and used xyFromCell to backwards extract the adjacent cell coordinates.
Does that do the trick for you?
Cheers,
Ben
### START
require(raster)
require(sp)
## Create a raster
r <- raster(nc=30, nr=30)
r <- setValues(r, round(runif(ncell(r))* 255))
plot(r)
##Given interesting points coordinates
xd <- c( -24.99270, 45.12069, 99.40321, 73.64419)
yd <- c(-45.435267, -88.369745, -7.086949, 44.174530)
pts <- data.frame(xd,yd)
pts_s<- SpatialPoints(pts)
projection(pts_s) <- projection(r)
points(pts_s, col="red", pch=16)
## Find pixels center of each point
N_cells <- cellFromXY(r, pts_s)
e <- adjacent(r, N_cells , directions='bishop', id=TRUE, sorted = TRUE)
xy <- xyFromCell(r, e[,'to'], spatial = TRUE)
#Visualization
plot(r)
points(pts_s, col="red", pch=16)
points(xy, col="black", pch=16)
### END
> On May 30, 2018, at 3:11 PM, ASANTOS via R-sig-Geo < [hidden email]> wrote:
>
> Dear R-Sig-Geo Members,
>
> I've like to extract xy coordinates from raster of 24 neigborhood cells that surround the 4 given points (pts_s) pixels and for this I used:
>
> #Packages
>
> require(raster)
> require(sp)
>
> ## Create a raster
> r <- raster(nc=30, nr=30)
> r <- setValues(r, round(runif(ncell(r))* 255))
> plot(r)
>
> ##Given interesting points coordinates
> xd <- c(-24.99270,45.12069,99.40321,73.64419)
> yd <- c(-45.435267,-88.369745,-7.086949,44.174530)
> pts <- data.frame(xd,yd)
> pts_s<- SpatialPoints(pts)
> points(pts_s, col="red", pch=16)
>
> ## Find pixels center of each point (My idea is not to use the original point coordinates, but coordinates of the center of interesting pixel).
> N_cells <- cellFromXY(r, pts_s)
>
>
> # Extract xy coordinates from raster of 24 neighborhood cells given pixel number N_cells
> e<-adjacent(r, N_cells , directions='bishop', id=TRUE)
> coordinates(land_mask)[e[,1],] ## Doesn't return 24 neighborhood by N_cells object
> ng_coords<-coordinates(land_mask)[e[,1],]
> #
>
> #Visualization
>
> plot(r)
> points(pts_s, col="red", pch=16)
> points(ng_coords, col="black", pch=16)
> ##
>
> But I don't have success because the ng_coords object is not a 24 neighborhood cells of each point that I search. There are solution for this?
>
> Thanks in advance,
>
> Alexandre
>
> --
> ======================================================================
> Alexandre dos Santos
> Proteção Florestal
> IFMT - Instituto Federal de Educação, Ciência e Tecnologia de Mato Grosso
> Campus Cáceres
> Caixa Postal 244
> Avenida dos Ramires, s/n
> Bairro: Distrito Industrial
> Cáceres - MT CEP: 78.200-000
> Fone: (+55) 65 99686-6970 (VIVO) (+55) 65 3221-2674 (FIXO)
>
> [hidden email]
> Lattes: http://lattes.cnpq.br/1360403201088680> OrcID: orcid.org/0000-0001-8232-6722
> Researchgate: www.researchgate.net/profile/Alexandre_Santos10
> LinkedIn: br.linkedin.com/in/alexandre-dos-santos-87961635
> Mendeley:www.mendeley.com/profiles/alexandre-dos-santos6/
>
> _______________________________________________
> R-sig-Geo mailing list
> [hidden email]
> https://stat.ethz.ch/mailman/listinfo/r-sig-geo>
Ben Tupper
Bigelow Laboratory for Ocean Sciences
60 Bigelow Drive, P.O. Box 380
East Boothbay, Maine 04544
http://www.bigelow.orgEcological Forecasting: https://eco.bigelow.org/ [[alternative HTML version deleted]]
_______________________________________________
R-sig-Geo mailing list
[hidden email]
https://stat.ethz.ch/mailman/listinfo/r-sig-geo
|
|
|
Or you can try something like this?
### START
require(raster)
require(sp)
r <- raster(nc=30, nr=30)
r <- setValues(r, round(runif(ncell(r))* 255))
xd <- c(-24.99270,45.12069,99.40321,73.64419)
yd <- c(-45.435267,-88.369745,-7.086949,44.174530)
pts <- data.frame(xd,yd)
pts_s<- SpatialPoints(pts)
N_cells <- cellFromXY(r, pts_s)
e<-adjacent(r, N_cells , directions='bishop', pairs=FALSE)
ng_coords <- xyFromCell(r, e)
plot(r)
points(pts, col='red', pch=16)
points(ng_coords, col='black', pch=16)
### Alternative to what Ben suggested!
## Set neighborhood matrix. Focal cell is 0 while neighbors are 1!!
neigh <- matrix(1L, nrow=5, ncol=5); neigh[3,3] <- 0L
e1<-adjacent(r, N_cells , directions=neigh, pairs=FALSE)
ng_coords1 <- xyFromCell(r, e1)
plot(r);
points(pts, col='red', pch=16);
points(ng_coords, col='black', pch=16);
points(ng_coords1, col='blue', pch=16)
### END
HTH,
Vijay.
On Wed, May 30, 2018 at 4:22 PM, Ben Tupper < [hidden email]> wrote:
> Hi,
>
> I'm not sure why you expect 24 points - you have 4 locations and for each
> you want the 4 bishop's directions - so, I think at most you should expect
> 16 points. See http://www.lpc.uottawa.ca/publications/moransi/moran.htm <
> http://www.lpc.uottawa.ca/publications/moransi/moran.htm> for where I
> expect 4 points for bishop's for each input location; perhaps you have a
> different idea of bishop's direction?
>
> Your second point [45.12069, -88.369745] is on to the southern edge of the
> raster - so it can't find points southward - only the 2 northward.
>
> Finally, it may not make any difference at all, but your pts_s has no
> coordinate reference. Below I show where I assign the same projection as
> your raster. I also don't have 'land_mask' so I reused 'r' and used
> xyFromCell to backwards extract the adjacent cell coordinates.
>
> Does that do the trick for you?
>
> Cheers,
> Ben
>
> ### START
> require(raster)
> require(sp)
>
> ## Create a raster
> r <- raster(nc=30, nr=30)
> r <- setValues(r, round(runif(ncell(r))* 255))
> plot(r)
>
> ##Given interesting points coordinates
> xd <- c( -24.99270, 45.12069, 99.40321, 73.64419)
> yd <- c(-45.435267, -88.369745, -7.086949, 44.174530)
> pts <- data.frame(xd,yd)
> pts_s<- SpatialPoints(pts)
> projection(pts_s) <- projection(r)
> points(pts_s, col="red", pch=16)
>
> ## Find pixels center of each point
> N_cells <- cellFromXY(r, pts_s)
>
> e <- adjacent(r, N_cells , directions='bishop', id=TRUE, sorted = TRUE)
> xy <- xyFromCell(r, e[,'to'], spatial = TRUE)
>
>
> #Visualization
>
> plot(r)
> points(pts_s, col="red", pch=16)
> points(xy, col="black", pch=16)
> ### END
>
>
>
>
>
> > On May 30, 2018, at 3:11 PM, ASANTOS via R-sig-Geo <
> [hidden email]> wrote:
> >
> > Dear R-Sig-Geo Members,
> >
> > I've like to extract xy coordinates from raster of 24 neigborhood
> cells that surround the 4 given points (pts_s) pixels and for this I used:
> >
> > #Packages
> >
> > require(raster)
> > require(sp)
> >
> > ## Create a raster
> > r <- raster(nc=30, nr=30)
> > r <- setValues(r, round(runif(ncell(r))* 255))
> > plot(r)
> >
> > ##Given interesting points coordinates
> > xd <- c(-24.99270,45.12069,99.40321,73.64419)
> > yd <- c(-45.435267,-88.369745,-7.086949,44.174530)
> > pts <- data.frame(xd,yd)
> > pts_s<- SpatialPoints(pts)
> > points(pts_s, col="red", pch=16)
> >
> > ## Find pixels center of each point (My idea is not to use the original
> point coordinates, but coordinates of the center of interesting pixel).
> > N_cells <- cellFromXY(r, pts_s)
> >
> >
> > # Extract xy coordinates from raster of 24 neighborhood cells given
> pixel number N_cells
> > e<-adjacent(r, N_cells , directions='bishop', id=TRUE)
> > coordinates(land_mask)[e[,1],] ## Doesn't return 24 neighborhood by
> N_cells object
> > ng_coords<-coordinates(land_mask)[e[,1],]
> > #
> >
> > #Visualization
> >
> > plot(r)
> > points(pts_s, col="red", pch=16)
> > points(ng_coords, col="black", pch=16)
> > ##
> >
> > But I don't have success because the ng_coords object is not a 24
> neighborhood cells of each point that I search. There are solution for this?
> >
> > Thanks in advance,
> >
> > Alexandre
> >
> > --
> > ======================================================================
> > Alexandre dos Santos
> > Proteção Florestal
> > IFMT - Instituto Federal de Educação, Ciência e Tecnologia de Mato Grosso
> > Campus Cáceres
> > Caixa Postal 244
> > Avenida dos Ramires, s/n
> > Bairro: Distrito Industrial
> > Cáceres - MT CEP: 78.200-000
> > Fone: (+55) 65 99686-6970 (VIVO) (+55) 65 3221-2674 (FIXO)
> >
> > [hidden email]
> > Lattes: http://lattes.cnpq.br/1360403201088680> > OrcID: orcid.org/0000-0001-8232-6722
> > Researchgate: www.researchgate.net/profile/Alexandre_Santos10
> > LinkedIn: br.linkedin.com/in/alexandre-dos-santos-87961635
> > Mendeley:www.mendeley.com/profiles/alexandre-dos-santos6/
> >
> > _______________________________________________
> > R-sig-Geo mailing list
> > [hidden email]
> > https://stat.ethz.ch/mailman/listinfo/r-sig-geo> >
>
> Ben Tupper
> Bigelow Laboratory for Ocean Sciences
> 60 Bigelow Drive, P.O. Box 380
> East Boothbay, Maine 04544
> http://www.bigelow.org>
> Ecological Forecasting: https://eco.bigelow.org/>
>
>
>
>
>
> [[alternative HTML version deleted]]
>
> _______________________________________________
> R-sig-Geo mailing list
> [hidden email]
> https://stat.ethz.ch/mailman/listinfo/r-sig-geo>
--
Vijay Lulla, Ph.D.
Assistant Professor,
Dept. of Geography, IUPUI
425 University Blvd, CA-207C.
Indianapolis, IN-46202
[hidden email]
< http://vijaylulla.com>
http://vijaylulla.com [[alternative HTML version deleted]]
_______________________________________________
R-sig-Geo mailing list
[hidden email]
https://stat.ethz.ch/mailman/listinfo/r-sig-geo
|
|
|
Thanks so much Vijay and Ben, now it works!!!
Originally, I expect 24 for each 4 point (96 total).
Apologies, in my example preparation I changed the raster objects
'land_mask' and 'r' and the idea of my second point [45.12069,
-88.369745] is to force NA results.
The code below is a solution that I expected:
### Alternative to what Ben suggested!
## Set neighborhood matrix. Focal cell is 0 while neighbors are 1!!
neigh <- matrix(1L, nrow=5, ncol=5); neigh[3,3] <- 0L
e1<-adjacent(r, N_cells , directions=neigh, pairs=FALSE)
ng_coords1 <- xyFromCell(r, e1)
plot(r);
points(pts, col='red', pch=16);
points(ng_coords, col='black', pch=16);
points(ng_coords1, col='blue', pch=16)
### END
--
======================================================================
Alexandre dos Santos
Proteção Florestal
IFMT - Instituto Federal de Educação, Ciência e Tecnologia de Mato Grosso
Campus Cáceres
Caixa Postal 244
Avenida dos Ramires, s/n
Bairro: Distrito Industrial
Cáceres - MT CEP: 78.200-000
Fone: (+55) 65 99686-6970 (VIVO) (+55) 65 3221-2674 (FIXO)
[hidden email]
Lattes: http://lattes.cnpq.br/1360403201088680OrcID: orcid.org/0000-0001-8232-6722
Researchgate: www.researchgate.net/profile/Alexandre_Santos10
LinkedIn: br.linkedin.com/in/alexandre-dos-santos-87961635
Mendeley:www.mendeley.com/profiles/alexandre-dos-santos6/
======================================================================
Em 30/05/2018 16:29, Vijay Lulla escreveu:
> Or you can try something like this?
>
> ### START
> require(raster)
> require(sp)
>
> r <- raster(nc=30, nr=30)
> r <- setValues(r, round(runif(ncell(r))* 255))
>
> xd <- c(-24.99270,45.12069,99.40321,73.64419)
> yd <- c(-45.435267,-88.369745,-7.086949,44.174530)
> pts <- data.frame(xd,yd)
> pts_s<- SpatialPoints(pts)
>
> N_cells <- cellFromXY(r, pts_s)
> e<-adjacent(r, N_cells , directions='bishop', pairs=FALSE)
>
> ng_coords <- xyFromCell(r, e)
> plot(r)
> points(pts, col='red', pch=16)
> points(ng_coords, col='black', pch=16)
>
>
[[elided Yahoo spam]]
[[elided Yahoo spam]]
> neigh <- matrix(1L, nrow=5, ncol=5); neigh[3,3] <- 0L
> e1<-adjacent(r, N_cells , directions=neigh, pairs=FALSE)
> ng_coords1 <- xyFromCell(r, e1)
> plot(r);
> points(pts, col='red', pch=16);
> points(ng_coords, col='black', pch=16);
> points(ng_coords1, col='blue', pch=16)
> ### END
>
> HTH,
> Vijay.
>
> On Wed, May 30, 2018 at 4:22 PM, Ben Tupper < [hidden email]
> <mailto: [hidden email]>> wrote:
>
> Hi,
>
> I'm not sure why you expect 24 points - you have 4 locations and
> for each you want the 4 bishop's directions - so, I think at most
> you should expect 16 points. See
> http://www.lpc.uottawa.ca/publications/moransi/moran.htm> < http://www.lpc.uottawa.ca/publications/moransi/moran.htm>
> < http://www.lpc.uottawa.ca/publications/moransi/moran.htm> < http://www.lpc.uottawa.ca/publications/moransi/moran.htm>> for
> where I expect 4 points for bishop's for each input location;
> perhaps you have a different idea of bishop's direction?
>
> Your second point [45.12069, -88.369745] is on to the southern
> edge of the raster - so it can't find points southward - only the
> 2 northward.
>
> Finally, it may not make any difference at all, but your pts_s has
> no coordinate reference. Below I show where I assign the same
> projection as your raster. I also don't have 'land_mask' so I
> reused 'r' and used xyFromCell to backwards extract the adjacent
> cell coordinates.
>
> Does that do the trick for you?
>
> Cheers,
> Ben
>
> ### START
> require(raster)
> require(sp)
>
> ## Create a raster
> r <- raster(nc=30, nr=30)
> r <- setValues(r, round(runif(ncell(r))* 255))
> plot(r)
>
> ##Given interesting points coordinates
> xd <- c( -24.99270, 45.12069, 99.40321, 73.64419)
> yd <- c(-45.435267, -88.369745, -7.086949, 44.174530)
> pts <- data.frame(xd,yd)
> pts_s<- SpatialPoints(pts)
> projection(pts_s) <- projection(r)
> points(pts_s, col="red", pch=16)
>
> ## Find pixels center of each point
> N_cells <- cellFromXY(r, pts_s)
>
> e <- adjacent(r, N_cells , directions='bishop', id=TRUE, sorted =
> TRUE)
> xy <- xyFromCell(r, e[,'to'], spatial = TRUE)
>
>
> #Visualization
>
> plot(r)
> points(pts_s, col="red", pch=16)
> points(xy, col="black", pch=16)
> ### END
>
>
>
>
>
> > On May 30, 2018, at 3:11 PM, ASANTOS via R-sig-Geo
> < [hidden email] <mailto: [hidden email]>> wrote:
> >
> > Dear R-Sig-Geo Members,
> >
> > I've like to extract xy coordinates from raster of 24
> neigborhood cells that surround the 4 given points (pts_s) pixels
> and for this I used:
> >
> > #Packages
> >
> > require(raster)
> > require(sp)
> >
> > ## Create a raster
> > r <- raster(nc=30, nr=30)
> > r <- setValues(r, round(runif(ncell(r))* 255))
> > plot(r)
> >
> > ##Given interesting points coordinates
> > xd <- c(-24.99270,45.12069,99.40321,73.64419)
> > yd <- c(-45.435267,-88.369745,-7.086949,44.174530)
> > pts <- data.frame(xd,yd)
> > pts_s<- SpatialPoints(pts)
> > points(pts_s, col="red", pch=16)
> >
> > ## Find pixels center of each point (My idea is not to use the
> original point coordinates, but coordinates of the center of
> interesting pixel).
> > N_cells <- cellFromXY(r, pts_s)
> >
> >
> > # Extract xy coordinates from raster of 24 neighborhood cells
> given pixel number N_cells
> > e<-adjacent(r, N_cells , directions='bishop', id=TRUE)
> > coordinates(land_mask)[e[,1],] ## Doesn't return 24 neighborhood
> by N_cells object
> > ng_coords<-coordinates(land_mask)[e[,1],]
> > #
> >
> > #Visualization
> >
> > plot(r)
> > points(pts_s, col="red", pch=16)
> > points(ng_coords, col="black", pch=16)
> > ##
> >
> > But I don't have success because the ng_coords object is not
> a 24 neighborhood cells of each point that I search. There are
> solution for this?
> >
> > Thanks in advance,
> >
> > Alexandre
> >
> > --
> >
> ======================================================================
> > Alexandre dos Santos
> > Proteção Florestal
> > IFMT - Instituto Federal de Educação, Ciência e Tecnologia de
> Mato Grosso
> > Campus Cáceres
> > Caixa Postal 244
> > Avenida dos Ramires, s/n
> > Bairro: Distrito Industrial
> > Cáceres - MT CEP: 78.200-000
> > Fone: (+55) 65 99686-6970 (VIVO) (+55) 65 3221-2674 (FIXO)
> >
> > [hidden email]
> <mailto: [hidden email]>
> > Lattes: http://lattes.cnpq.br/1360403201088680> < http://lattes.cnpq.br/1360403201088680>
> > OrcID: orcid.org/0000-0001-8232-6722
> < http://orcid.org/0000-0001-8232-6722>
> > Researchgate: www.researchgate.net/profile/Alexandre_Santos10
> < http://www.researchgate.net/profile/Alexandre_Santos10>
> > LinkedIn: br.linkedin.com/in/alexandre-dos-santos-87961635
> < http://br.linkedin.com/in/alexandre-dos-santos-87961635>
> > Mendeley:www.mendeley.com/profiles/alexandre-dos-santos6/
> < http://www.mendeley.com/profiles/alexandre-dos-santos6/>
> >
> > _______________________________________________
> > R-sig-Geo mailing list
> > [hidden email] <mailto: [hidden email]>
> > https://stat.ethz.ch/mailman/listinfo/r-sig-geo> < https://stat.ethz.ch/mailman/listinfo/r-sig-geo>
> >
>
> Ben Tupper
> Bigelow Laboratory for Ocean Sciences
> 60 Bigelow Drive, P.O. Box 380
> East Boothbay, Maine 04544
> http://www.bigelow.org>
> Ecological Forecasting: https://eco.bigelow.org/>
>
>
>
>
>
> [[alternative HTML version deleted]]
>
> _______________________________________________
> R-sig-Geo mailing list
> [hidden email] <mailto: [hidden email]>
> https://stat.ethz.ch/mailman/listinfo/r-sig-geo> < https://stat.ethz.ch/mailman/listinfo/r-sig-geo>
>
>
>
>
> --
> Vijay Lulla, Ph.D.
>
> Assistant Professor,
> Dept. of Geography, IUPUI
> 425 University Blvd, CA-207C.
> Indianapolis, IN-46202
> [hidden email] <mailto: [hidden email]>
>
> < http://vijaylulla.com>
> http://vijaylulla.com [[alternative HTML version deleted]]
_______________________________________________
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