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Converting line vector layer to raster with pixellate.psp creating missing data?
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The following example converts a line vector layer (road network) into a density raster. It seems to be working for others', but it looks like it's creating data gaps at my resolution (50m).
library(spatstat)
library(raster)
library(rgdal)
library(magrittr)
# Set common CRS
crs <- "+proj=utm +zone=10 +ellps=GRS80 +datum=NAD83 +units=m +no_defs "
# Read in our vector & raster data
rast <- readRDS(gzcon(url('http://web.pdx.edu/~porlando/study_area.RDS'))) %>%
spTransform(CRSobj = crs) %>% raster(res = 50, crs = crs)
vect <- readRDS(gzcon(url('http://web.pdx.edu/~porlando/fwy.RDS'))) %>%
spTransform(CRSobj = crs) %>% crop(rast)
# Use spatstat to create density raster
roadsPSP <- as.psp(as(vect, "SpatialLines"))
roadLengthIM <- pixellate.psp(roadsPSP, eps = 50) # meters
roadLengthRaster <- raster(roadLengthIM, crs = projection(vect))
# The resolution isn't exactly 50m x 50m so I resample again
roadLengthRaster50m <- resample(roadLengthRaster, rast)
# Recode values to exaggerate presence/absence
values(roadLengthRaster50m)[values(roadLengthRaster50m)<=0] <- NA
values(roadLengthRaster50m)[values(roadLengthRaster50m)>0] <- 100
# Plot raster layer on top of vector layer
plot(vect, col="black")
plot(roadLengthRaster50m, add = T)
There are many areas where the black vector layer is poking through the rasterized version. At this point, I'm not sure whether it's a visualization issue, or a limitation of this approach entirely!
raster r rasterization density spatstat
add a comment |
The following example converts a line vector layer (road network) into a density raster. It seems to be working for others', but it looks like it's creating data gaps at my resolution (50m).
library(spatstat)
library(raster)
library(rgdal)
library(magrittr)
# Set common CRS
crs <- "+proj=utm +zone=10 +ellps=GRS80 +datum=NAD83 +units=m +no_defs "
# Read in our vector & raster data
rast <- readRDS(gzcon(url('http://web.pdx.edu/~porlando/study_area.RDS'))) %>%
spTransform(CRSobj = crs) %>% raster(res = 50, crs = crs)
vect <- readRDS(gzcon(url('http://web.pdx.edu/~porlando/fwy.RDS'))) %>%
spTransform(CRSobj = crs) %>% crop(rast)
# Use spatstat to create density raster
roadsPSP <- as.psp(as(vect, "SpatialLines"))
roadLengthIM <- pixellate.psp(roadsPSP, eps = 50) # meters
roadLengthRaster <- raster(roadLengthIM, crs = projection(vect))
# The resolution isn't exactly 50m x 50m so I resample again
roadLengthRaster50m <- resample(roadLengthRaster, rast)
# Recode values to exaggerate presence/absence
values(roadLengthRaster50m)[values(roadLengthRaster50m)<=0] <- NA
values(roadLengthRaster50m)[values(roadLengthRaster50m)>0] <- 100
# Plot raster layer on top of vector layer
plot(vect, col="black")
plot(roadLengthRaster50m, add = T)
There are many areas where the black vector layer is poking through the rasterized version. At this point, I'm not sure whether it's a visualization issue, or a limitation of this approach entirely!
raster r rasterization density spatstat
add a comment |
The following example converts a line vector layer (road network) into a density raster. It seems to be working for others', but it looks like it's creating data gaps at my resolution (50m).
library(spatstat)
library(raster)
library(rgdal)
library(magrittr)
# Set common CRS
crs <- "+proj=utm +zone=10 +ellps=GRS80 +datum=NAD83 +units=m +no_defs "
# Read in our vector & raster data
rast <- readRDS(gzcon(url('http://web.pdx.edu/~porlando/study_area.RDS'))) %>%
spTransform(CRSobj = crs) %>% raster(res = 50, crs = crs)
vect <- readRDS(gzcon(url('http://web.pdx.edu/~porlando/fwy.RDS'))) %>%
spTransform(CRSobj = crs) %>% crop(rast)
# Use spatstat to create density raster
roadsPSP <- as.psp(as(vect, "SpatialLines"))
roadLengthIM <- pixellate.psp(roadsPSP, eps = 50) # meters
roadLengthRaster <- raster(roadLengthIM, crs = projection(vect))
# The resolution isn't exactly 50m x 50m so I resample again
roadLengthRaster50m <- resample(roadLengthRaster, rast)
# Recode values to exaggerate presence/absence
values(roadLengthRaster50m)[values(roadLengthRaster50m)<=0] <- NA
values(roadLengthRaster50m)[values(roadLengthRaster50m)>0] <- 100
# Plot raster layer on top of vector layer
plot(vect, col="black")
plot(roadLengthRaster50m, add = T)
There are many areas where the black vector layer is poking through the rasterized version. At this point, I'm not sure whether it's a visualization issue, or a limitation of this approach entirely!
raster r rasterization density spatstat
The following example converts a line vector layer (road network) into a density raster. It seems to be working for others', but it looks like it's creating data gaps at my resolution (50m).
library(spatstat)
library(raster)
library(rgdal)
library(magrittr)
# Set common CRS
crs <- "+proj=utm +zone=10 +ellps=GRS80 +datum=NAD83 +units=m +no_defs "
# Read in our vector & raster data
rast <- readRDS(gzcon(url('http://web.pdx.edu/~porlando/study_area.RDS'))) %>%
spTransform(CRSobj = crs) %>% raster(res = 50, crs = crs)
vect <- readRDS(gzcon(url('http://web.pdx.edu/~porlando/fwy.RDS'))) %>%
spTransform(CRSobj = crs) %>% crop(rast)
# Use spatstat to create density raster
roadsPSP <- as.psp(as(vect, "SpatialLines"))
roadLengthIM <- pixellate.psp(roadsPSP, eps = 50) # meters
roadLengthRaster <- raster(roadLengthIM, crs = projection(vect))
# The resolution isn't exactly 50m x 50m so I resample again
roadLengthRaster50m <- resample(roadLengthRaster, rast)
# Recode values to exaggerate presence/absence
values(roadLengthRaster50m)[values(roadLengthRaster50m)<=0] <- NA
values(roadLengthRaster50m)[values(roadLengthRaster50m)>0] <- 100
# Plot raster layer on top of vector layer
plot(vect, col="black")
plot(roadLengthRaster50m, add = T)
There are many areas where the black vector layer is poking through the rasterized version. At this point, I'm not sure whether it's a visualization issue, or a limitation of this approach entirely!
raster r rasterization density spatstat
raster r rasterization density spatstat
asked 4 mins ago
spacedSparkingspacedSparking
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