[R-sig-Geo] apply a formula by matrix
Hi, I've to apply a formula to a raster in relation to an index table created from raster stack. I'm trying to explain the problem: I've three raster with same resolution, that I join in a raster RasterStack, and from it I can obtain a table like this: > data <- stack(dem,aer550,aer550_type) > unique(as.matrix(data)) layer_1 layer_2 layer_3 [1,] 1 0.246000 2 [2,] 1 0.184500 2 [3,] 1 0.01 2 [4,] 0 0.01 2 [5,] 1 0.147600 2 [6,] 1 0.01 0 [7,] 0 0.01 0 . >From this table I develop a linear model that after I've to apply to another raster that isn't in the raster stack and it has a higher resolution. I've to compute the function for the raster with higher resolution, according to the coefficients of the rows, and only for specific pixels.(layer_1 = 1 AND layer_2 = 0.246 AND layer_3 = 2) --> function ( -0.2710751 0.7981552 ) layer_1 layer_2 layer_3coeff_model_1 coeff_model_2 11 0.246000 2 -0.2710751 0.7981552 21 0.184500 2 -1.1499351 -0.6216590 31 0.01 2 -0.6643215 0.1993647 40 0.01 2 -1.0418143 1.5379033 51 0.147600 2 2.3148048 0.8951158 61 0.01 0 -0.2710751 0.7981552 70 0.01 0 -1.1499351 -0.6216590 ... ... Thanks in advance, Alfredo ___ R-sig-Geo mailing list R-sig-Geo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
[R-sig-Geo] how to get a SpatialGrid object from a .gri file ?
Hello I got a .gri file (data about density of population in Ireland from http://www.diva-gis.org/gdata) that I would like to read with the readGDAL function from the *rgdal* package. So have I to get a SpatialGrid object from this file. Could you tell me if it's possible to do that with the * rgdal* package (because I didn't succeed in...) ? I was told to use the * raster* package but I would like to do so thanks to the *rgdal* package, downloading as few packages more as possible. Thank you for your help. Yours sincerely, Camille Garcin [[alternative HTML version deleted]] ___ R-sig-Geo mailing list R-sig-Geo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
[R-sig-Geo] spatial modelling Lectureship at the University of Bristol
Dear list, Please see below an announcement about a job opening in the School of Geographical Sciences at the University of Bristol. The post is only just being advertised today, but there is a need to have someone in post by October -- so there is a very short time before the deadline. Subscribers to this list looking for a beginning academic appointment in the social sciences would be very appropriate applicants. Please be aware the post is for three years. - Malcolm Dr Malcolm Fairbrother Lecturer School of Geographical Sciences University of Bristol ___ Lecturer in Quantitative Geography (vacancy ref. 16443) The School of Geographical Sciences is looking to appoint an enthusiastic and committed person to a Lectureship in Quantitative Geography. You will deliver teaching in quantitative methods at both undergraduate and postgraduate levels, as well as other substantive areas of human geography. You will be able to teach regression methods, ideally through the medium of R. The post is advertised at three years in the first instance, and you will need to develop your own research agenda, contribute to initiatives within the Spatial Modelling research group, and participate in the range of activities in the School as well as building strong research links more broadly. You will become a member of the Spatial Modelling Research Group (www.bris.ac.uk/geography/research/spatial-modelling/) which has an international reputation as a leading centre for spatial analysis. It focuses on innovative methodologies and techniques for the analysis of spatial data and their application to social, political and economic research problems. In addition the Group has a strong interest in the development of innovative social science software. This Lectureship offers an exciting opportunity to join this innovative research group and to contribute to future developments in the School of Geographical Sciences. Applications are welcomed from both human geographers and social scientists in cognate disciplines who have research interests in quantitative analysis in the social sciences using geographical data. You will have an emerging international reputation for research (or will be able to demonstrate a capacity to build such a reputation) and an excellent record of publication for their career stage. Grade : Level b in Pathway 1 Salary : £33,734 Please see: http://www.bris.ac.uk/boris/jobs/feeds/ads?ID=98491 ___ R-sig-Geo mailing list R-sig-Geo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
[R-sig-Geo] plot3D raster coordinates
Hi list, I'd like to plot3D() a raster layer using it's own coordinates instead of the row-col system so I can easily add points. Here's a demo library(raster) library(rgl) r <- raster(matrix(1, nrow = 5, ncol = 5)) extent(r) # class : Extent # xmin: 0 # xmax: 1 # ymin: 0 # ymax: 1 plot(r) points(0.5, 0.5) # centre of the raster plot3D(r) decorate3d() rgl.points(0.5, 0.5, 1.5, col = 2) # wrong rgl.points(3.5, 3.5, 1.5, col = 1) # it's row-col coordinates Thanks, Etienne [[alternative HTML version deleted]] ___ R-sig-Geo mailing list R-sig-Geo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
Re: [R-sig-Geo] plot3D raster coordinates
I don't know if this will clarify or add to the confusion as I don't know if
it's the same issue or another one with the same effect, but when using a
projected raster, I get some weird coordinates in 3d (really large). I can't
see how it is linked to my raster coordinates.
Example :
library(raster)
library(rgl)
new("RasterLayer"
, file = new(".RasterFile"
, name = ""
, datanotation = "FLT4S"
, byteorder = "little"
, nodatavalue = -Inf
, nbands = 1L
, bandorder = "BIL"
, offset = 0L
, toptobottom = TRUE
, driver = ""
)
, data = new(".SingleLayerData"
, values = c(2.7659912109375, 2.07601928710938, 1.8389648438,
1.7440185546875,
1.6610107421875, 2.28298950195312, 3.67398071289062, 2.23001098632812,
2.50997924804688, 2.92999267578125, 2.22100830078125, 2.83200073242188,
4.6510009765625, 3.69601440429688, 3.20401000976562, 2.7750244140625,
2.1190185546875, 3.20901489257812, 5.39801025390625, 4.65200805664062,
3.69699096679688, 3.25399780273438, 1.98800659179688, 3.38198852539062,
5.93698120117188, 3.697021484375, 1.6610351562, 1.60601806640625,
0.739013671875, 1.7080078125, 7.50399780273438, 1.34100341796875,
0.93597412109375, 1.01699829101562, 1.02999877929688, 0.813995361328125
)
, offset = 0
, gain = 1
, inmemory = TRUE
, fromdisk = FALSE
, isfactor = FALSE
, attributes = list()
, haveminmax = TRUE
, min = 0.739013671875
, max = 7.50399780273438
, band = 1L
)
, legend = new(".RasterLegend"
, type = character(0)
, values = NULL
, color = NULL
, names = NULL
, colortable = NULL
)
, history = character(0)
, title = character(0)
, extent = new("Extent"
, xmin = 337879.01907
, xmax = 337882.01907
, ymin = 5386659.0191
, ymax = 5386662.0191
)
, rotated = FALSE
, rotation = new(".Rotation"
, geotrans = numeric(0)
, transfun = function ()
NULL
)
, ncols = 6L
, nrows = 6L
, crs = new("CRS"
, projargs = " +proj=tmerc +lat_0=0 +lon_0=-67.5 +k=0. +x_0=304800
+y_0=0 +ellps=GRS80 +datum=NAD83 +units=m +no_defs +towgs84=0,0,0"
)
, layernames = "1271"
, z = list()
, zname = ""
, zvalue = ""
, unit = ""
)
plot(r2)
points(337880, 5386659.5)
plot3D(r2)
decorate3d() # the coordinates are really large
rgl.points(337880, 5386659.5, 10, col=1) # doesn't match with the raster
Etienne
2011/7/7 Etienne B. Racine
> Hi list,
>
> I'd like to plot3D() a raster layer using it's own coordinates instead of
> the row-col system so I can easily add points.
> Here's a demo
>
> library(raster)
> library(rgl)
>
> r <- raster(matrix(1, nrow = 5, ncol = 5))
> extent(r)
> # class : Extent
> # xmin: 0
> # xmax: 1
> # ymin: 0
> # ymax: 1
> plot(r)
> points(0.5, 0.5) # centre of the raster
>
>
> plot3D(r)
> decorate3d()
> rgl.points(0.5, 0.5, 1.5, col = 2) # wrong
> rgl.points(3.5, 3.5, 1.5, col = 1) # it's row-col coordinates
>
> Thanks,
> Etienne
>
>
[[alternative HTML version deleted]]
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[R-sig-Geo] Error in anyDuplicated.default(coords) message with trinb
Hi everyone,
I'm attempting to do some spatial analyses with a relatively simple data
set and I'm running into some issues. Here's my code:
sosp09 <- read.csv("f:\\sosp\\2009\\sosp09.means.csv", header=T)
sp.point <- cbind(sosp09$x, sosp09$y)
colnames(sp.point) <- c("LONG","LAT")
# Projection: UTM Zone 17
proj <- CRS("+proj=utm +zone=18 +datum=WGS84")
# Create spatial object
data.sp <- SpatialPointsDataFrame(coords=sp.point, data=sosp09,
proj4string=proj)
## Bounding box of data points
bbox(data.sp)
#build neighborhood
sosp.neigh <- tri2nb(data.sp)
And, with the last step, I get
Error in anyDuplicated.default(coords) :
anyDuplicated() applies only to vectors
I went through and removed duplicated rows by averaging the responses
and I still get this message. I also removed via rm() all the objected
from the original analysis and I still get this message. Any ideas
what's going on?
Thanks,
Jeff
The data:
new("SpatialPointsDataFrame"
, data = structure(list(band = c(6467L, 6483L, 6466L, 6465L, 6463L,
6462L,
6498L, 6443L, 6496L, 6495L, 6459L, NA, 6458L, 6491L, 6446L, 6464L,
NA, 6473L, 6444L, 6457L, 6468L, NA, 6485L, 6474L, 6445L, 6486L,
6488L, 6472L, 6493L, 6492L, 6471L, 6449L, 6453L, 6460L, 6482L
), site = structure(c(19L, 26L, 18L, 17L, 15L, 14L, 35L, 1L,
34L, 33L, 12L, 8L, 11L, 30L, 4L, 16L, 5L, 23L, 2L, 10L, 20L,
9L, 27L, 24L, 3L, 28L, 29L, 22L, 32L, 31L, 21L, 6L, 7L, 13L,
25L), .Label = c("SOSP0901", "SOSP0902", "SOSP0903", "SOSP0904",
"SOSP0905", "SOSP0906", "SOSP0908", "SOSP0909", "SOSP0910", "sosp0911",
"sosp0912", "sosp0913", "sosp0914", "SOSP0915", "SOSP0916", "SOSP0917",
"SOSP0918", "SOSP0919", "SOSP0920", "SOSP0921", "SOSP0925", "SOSP0926",
"SOSP0927", "SOSP0928", "Sosp0934", "Sosp0935", "Sosp0936", "Sosp0937",
"Sosp0938", "Sosp0940", "Sosp0941", "Sosp0942", "Sosp0943", "Sosp0944",
"Sosp0946"), class = "factor"), sex = structure(c(1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L
), .Label = "M", class = "factor"), age = structure(c(1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L), .Label = "AHY", class = "factor"), wing = c(66, 62, 66,
65, 65, 64.5, 66, 69, 64.5, 67.5, 66, 66.5, 68, 67, 66, 67, 64.5,
68, 65, 65, 66, 65.5, 65, 66, 64, 65, 65, 66, 66, 63, 67, 66,
66, 65, 64), tail = c(69, 67, 69, 66, 67, 65, 66, 68, 64, 67.5,
66, 66, 67, 67, 67, 70, 69, 64, 67, 69, 68, 65.5, 66, 67, 65,
66, 66, 68, 71, 55, 72, 62, 70, 70, 66), bill = c(9, 9.7, 9.6,
9.5, 9.6, 8.5, 9.2, 9.5, 8.4, 9.2, 9.9, 8.8, 8.8, 9.2, 8.6, 9.6,
9.15, 9.7, 9.7, 8.7, 8.9, 9.45, 8.8, 9.1, 9.2, 9.2, 9.1, 8.9,
9.6, 8.7, 9.2, 8.8, 9.2, 9, 9.3), tarsus = c(21.6, 20.6, 20.9,
21.8, 20.9, 19.6, 22, 21.5, 21.7, 21.3, 22.1, 21.15, 19.9, 22.4,
22, 20.1, 21.85, 21.6, 20.9, 21.5, 22.4, 21.5, 21.3, 21.2, 21.5,
20.6, 21.4, 21.4, 21.4, 21.7, 21.4, 21.1, 20.6, 20.1, 22.2),
mass = c(20.8, 20.6, 21.1, 22.3, NA, 16.7, 23, 23.2, 20.7,
20.9, 27.3, 21.1, 21.4, 24.3, 23.2, 21.7, 22, 21, NA, 20.1,
20.5, 21.4, 20.5, 23.3, 21.5, 20.5, 20.8, 21, 21.3, 20.3,
20.4, 21, 22.9, 19.7, 21.5), x = c(1647222L, 1648242L, 1648272L,
1648422L, 1651242L, 1652472L, 1652472L, 1653042L, 1653282L,
1653372L, 1654092L, 1654212L, 1654362L, 1655082L, 1657032L,
1657212L, 1657272L, 1657932L, 1658292L, 1658412L, 1658772L,
1659072L, 1659192L, 1659342L, 1659702L, 1659762L, 1659912L,
1660692L, 1660872L, 1661022L, 1661082L, 1662042L, 1662192L,
1663362L, 1663512L), y = c(2207359L, 2206909L, 2207479L,
2202859L, 2203219L, 2204599L, 2198299L, 2194849L, 2202889L,
2208229L, 2199469L, 2199649L, 2199769L, 2202589L, 2198089L,
2201449L, 2198029L, 2201209L, 2202529L, 2201989L, 2203549L,
2202529L, 2203519L, 2201209L, 2202499L, 2204179L, 2203459L,
2200939L, 2208469L, 2208709L, 2201419L, 2204299L, 2204989L,
2206339L, 2202619L), urban1 = c(0.1724138, 0.2068966, 0.06896552,
0.2413793, 0.5172413, 0.34482762, 0.55172422, 0.138, 0.06896552,
0.03448276, 0.06896552, 1, 0.9655172, 0.4827586, 0.966, 0.8965516,
0.31, 1, 1, 0.9996, 0.79310346, 1, 1.0012, 0.9992,
1, 0.9998, 1, 0.999, 0.48275866, 1, 1.001, 1,
1, 1, 0.7241379), urban2 = c(0.2214765, 0.12751683, 0.18791945,
0.09395973, 0.24832219, 0.1946309, 0.32885906, 0.315, 0.08724833,
0.05369128, 0.3959732, 0.583892609, 0.77181212, 0.42281877,
0.758, 0.6577181, 0.564, 1.0014, 0.993, 0.9997, 0.63758395,
0.7919463, 1.0003, 1, 1, 1.001, 0.73154363, 1.0004,
0.59731537, 0.8993289, 0.97315443, 1, 0.913, 1.0001,
0.75838925), urbank = c(0.0976826, 0.210325588, 0.360516315,
0.063361691, 0.060721623, 0.23995307, 0.18979175, 0.275,
0.065708423, 0.1589909, 0.33294
Re: [R-sig-Geo] Error in anyDuplicated.default(coords) message with trinb
Jeff, ?tri2nb suggests you to try
tri2nb(coordinates(data.sp))
On 07/07/2011 03:52 PM, Stratford, Jeffrey wrote:
> Hi everyone,
>
>
>
> I'm attempting to do some spatial analyses with a relatively simple data
> set and I'm running into some issues. Here's my code:
>
>
>
> sosp09 <- read.csv("f:\\sosp\\2009\\sosp09.means.csv", header=T)
>
> sp.point <- cbind(sosp09$x, sosp09$y)
>
> colnames(sp.point) <- c("LONG","LAT")
>
> # Projection: UTM Zone 17
>
> proj <- CRS("+proj=utm +zone=18 +datum=WGS84")
>
> # Create spatial object
>
> data.sp <- SpatialPointsDataFrame(coords=sp.point, data=sosp09,
> proj4string=proj)
>
> ## Bounding box of data points
>
> bbox(data.sp)
>
> #build neighborhood
>
> sosp.neigh <- tri2nb(data.sp)
>
>
>
> And, with the last step, I get
>
>
>
> Error in anyDuplicated.default(coords) :
>
> anyDuplicated() applies only to vectors
>
>
>
> I went through and removed duplicated rows by averaging the responses
> and I still get this message. I also removed via rm() all the objected
> from the original analysis and I still get this message. Any ideas
> what's going on?
>
>
>
> Thanks,
>
>
>
> Jeff
>
>
>
> The data:
>
>
>
>
>
> new("SpatialPointsDataFrame"
>
> , data = structure(list(band = c(6467L, 6483L, 6466L, 6465L, 6463L,
> 6462L,
>
> 6498L, 6443L, 6496L, 6495L, 6459L, NA, 6458L, 6491L, 6446L, 6464L,
>
> NA, 6473L, 6444L, 6457L, 6468L, NA, 6485L, 6474L, 6445L, 6486L,
>
> 6488L, 6472L, 6493L, 6492L, 6471L, 6449L, 6453L, 6460L, 6482L
>
> ), site = structure(c(19L, 26L, 18L, 17L, 15L, 14L, 35L, 1L,
>
> 34L, 33L, 12L, 8L, 11L, 30L, 4L, 16L, 5L, 23L, 2L, 10L, 20L,
>
> 9L, 27L, 24L, 3L, 28L, 29L, 22L, 32L, 31L, 21L, 6L, 7L, 13L,
>
> 25L), .Label = c("SOSP0901", "SOSP0902", "SOSP0903", "SOSP0904",
>
> "SOSP0905", "SOSP0906", "SOSP0908", "SOSP0909", "SOSP0910", "sosp0911",
>
> "sosp0912", "sosp0913", "sosp0914", "SOSP0915", "SOSP0916", "SOSP0917",
>
> "SOSP0918", "SOSP0919", "SOSP0920", "SOSP0921", "SOSP0925", "SOSP0926",
>
> "SOSP0927", "SOSP0928", "Sosp0934", "Sosp0935", "Sosp0936", "Sosp0937",
>
> "Sosp0938", "Sosp0940", "Sosp0941", "Sosp0942", "Sosp0943", "Sosp0944",
>
> "Sosp0946"), class = "factor"), sex = structure(c(1L, 1L, 1L,
>
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
>
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L
>
> ), .Label = "M", class = "factor"), age = structure(c(1L, 1L,
>
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
>
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
>
> 1L), .Label = "AHY", class = "factor"), wing = c(66, 62, 66,
>
> 65, 65, 64.5, 66, 69, 64.5, 67.5, 66, 66.5, 68, 67, 66, 67, 64.5,
>
> 68, 65, 65, 66, 65.5, 65, 66, 64, 65, 65, 66, 66, 63, 67, 66,
>
> 66, 65, 64), tail = c(69, 67, 69, 66, 67, 65, 66, 68, 64, 67.5,
>
> 66, 66, 67, 67, 67, 70, 69, 64, 67, 69, 68, 65.5, 66, 67, 65,
>
> 66, 66, 68, 71, 55, 72, 62, 70, 70, 66), bill = c(9, 9.7, 9.6,
>
> 9.5, 9.6, 8.5, 9.2, 9.5, 8.4, 9.2, 9.9, 8.8, 8.8, 9.2, 8.6, 9.6,
>
> 9.15, 9.7, 9.7, 8.7, 8.9, 9.45, 8.8, 9.1, 9.2, 9.2, 9.1, 8.9,
>
> 9.6, 8.7, 9.2, 8.8, 9.2, 9, 9.3), tarsus = c(21.6, 20.6, 20.9,
>
> 21.8, 20.9, 19.6, 22, 21.5, 21.7, 21.3, 22.1, 21.15, 19.9, 22.4,
>
> 22, 20.1, 21.85, 21.6, 20.9, 21.5, 22.4, 21.5, 21.3, 21.2, 21.5,
>
> 20.6, 21.4, 21.4, 21.4, 21.7, 21.4, 21.1, 20.6, 20.1, 22.2),
>
> mass = c(20.8, 20.6, 21.1, 22.3, NA, 16.7, 23, 23.2, 20.7,
>
> 20.9, 27.3, 21.1, 21.4, 24.3, 23.2, 21.7, 22, 21, NA, 20.1,
>
> 20.5, 21.4, 20.5, 23.3, 21.5, 20.5, 20.8, 21, 21.3, 20.3,
>
> 20.4, 21, 22.9, 19.7, 21.5), x = c(1647222L, 1648242L, 1648272L,
>
> 1648422L, 1651242L, 1652472L, 1652472L, 1653042L, 1653282L,
>
> 1653372L, 1654092L, 1654212L, 1654362L, 1655082L, 1657032L,
>
> 1657212L, 1657272L, 1657932L, 1658292L, 1658412L, 1658772L,
>
> 1659072L, 1659192L, 1659342L, 1659702L, 1659762L, 1659912L,
>
> 1660692L, 1660872L, 1661022L, 1661082L, 1662042L, 1662192L,
>
> 1663362L, 1663512L), y = c(2207359L, 2206909L, 2207479L,
>
> 2202859L, 2203219L, 2204599L, 2198299L, 2194849L, 2202889L,
>
> 2208229L, 2199469L, 2199649L, 2199769L, 2202589L, 2198089L,
>
> 2201449L, 2198029L, 2201209L, 2202529L, 2201989L, 2203549L,
>
> 2202529L, 2203519L, 2201209L, 2202499L, 2204179L, 2203459L,
>
> 2200939L, 2208469L, 2208709L, 2201419L, 2204299L, 2204989L,
>
> 2206339L, 2202619L), urban1 = c(0.1724138, 0.2068966, 0.06896552,
>
> 0.2413793, 0.5172413, 0.34482762, 0.55172422, 0.138, 0.06896552,
>
> 0.03448276, 0.06896552, 1, 0.9655172, 0.4827586, 0.966, 0.8965516,
>
> 0.31, 1, 1, 0.9996, 0.79310346, 1, 1.0012, 0.9992,
>
> 1, 0.9998, 1, 0.999, 0.48275866, 1, 1.001, 1,
>
> 1, 1, 0.7241379), urban2 = c(0.2214765, 0.12751683, 0.18791945,
>
> 0.09395973, 0.24832219, 0.1946309, 0.32885906
[R-sig-Geo] Mapping contours from jpg map
Dear all, I have a jpg map of altitudinal contours in my study area which I would like to map and use in R to calculate the altitude and slope of GPS coordinates. So far, I have painstakingly traced these contours in ArcMap to create a shapefile (of polylines) with altitude. I have now imported this file shapefile into R. What I would like to do is turn it into a raster of slope and altitude, but I can't seem to find any method of doing this in the online R help archives. Does anyone have any idea which package I should be using, or perhaps if it is even possible to turn this type of shapefile into a raster? Thanks in advance! Sarah -- Imperial College London http://www.iccs.org.uk/sarahpapworth.htm ___ R-sig-Geo mailing list R-sig-Geo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
Re: [R-sig-Geo] Mapping contours from jpg map
On Thu, Jul 7, 2011 at 5:25 PM, Sarah Papworth wrote: > Dear all, > > I have a jpg map of altitudinal contours in my study area which I > would like to map and use in R to calculate the altitude and slope of > GPS coordinates. > So far, I have painstakingly traced these contours in ArcMap to create > a shapefile (of polylines) with altitude. I have now imported this > file shapefile into R. > > What I would like to do is turn it into a raster of slope and > altitude, but I can't seem to find any method of doing this in the > online R help archives. Does anyone have any idea which package I > should be using, or perhaps if it is even possible to turn this type > of shapefile into a raster? There's definitely tools for doing this in GRASS-GIS: http://linfiniti.com/2010/12/3d-visualisation-and-dem-creation-in-qgis-with-the-grass-plugin/ but not sure about R. One approach might be: load shapefile into R as a SpatialLinesDataFrame, so that each line has its height attribute. consider a grid of points over the space, and use rgeos functions to find the nearest contour line and its height. Assign height to that grid point. That will give you a grid that will look a bit like terraces between the contours, which you could possibly then smooth, although there may be systematic errors with this method... I suspect there's a better way by looking at more than one nearby contour line and doing some interpolation Actually the GRASS algorithms are discussed here: http://grass.osgeo.org/wiki/Contour_lines_to_DEM Barry ___ R-sig-Geo mailing list R-sig-Geo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
Re: [R-sig-Geo] Mapping contours from jpg map
> I suspect there's a better way by looking at more than one nearby > contour line and doing some interpolation I've got fairly good algorithm going now, but it requires a bit of modification of some sp package code. Currently spsample can return random or regular points on a line, but doesn't tell you which line the point came from. Hence there's no way to get the height of that line. But a bit of tweaking to the sampling code fixes that. My modification returns a spatial points data frame of points and line IDs. I'll not post that code here yet because Roger usually knows ways of doing my hacky things without hacking. I know that overlay() won't do it for you... Anyway, then I can get a set of (x,y,height) points on the contour lines, and then use any standard interpolation function (interp from akima for example) to get a grid. Looks pretty good, and also pretty quick. A 500x500 grid from a contour set with 212 contour lines is pretty instantaneous. Barry ___ R-sig-Geo mailing list R-sig-Geo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
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[R-sig-Geo] GLS model
Dear all, I have been using the GLS model provided by nlme package in R. I was wondering if it is possible to estimate an equivalent of R square for GLS in any R package. Nlme package did not provide such estimations. The only application that I found is Spatial Modeling Environment (SME). Thank you very much! Best, Yiching Yiching Lin, Ph.D. Assistant Professor Department of Life Science Tunghai University No. 181, Sec. 3 Taichung Port Rd., Taichung 40704, Taiwan Phone: +886-4-2590121 ext. 32406 Fax: +886-4-23590296 ___ R-sig-Geo mailing list R-sig-Geo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
