I have a NetCDF file of salinity in Indonesia water with 4 dimension (lon, lat, depth and time). I would like to create a map from my data, but it's appear not in appropriate position that not exactly match with the coastline.
download data here: https://onedrive.live.com/redir?resid=6FFDD661570C7D0A%21177
output map here: https://onedrive.live.com/redir?resid=6FFDD661570C7D0A%21176
# This is my script
library (ncdf)
library (raster)
library (sp)
setwd ('D:/work')
bio <- open.ncdf('data.nc')
print (bio)
sal.dat <- get.var.ncdf(bio,"salinity")
sal0 <- brick(sal.dat[,,1,])
extent(sal0) <- c(105,110,-5,0)
projection(sal0) <- CRS("+proj=longlat +datum=WGS84")
#plot image
image (sal0)
# load coastal lines of Indonesia:
con <- url("http://biogeo.ucdavis.edu/data/gadm2/R/IDN_adm0.RData")
load(file = con)
close(con)
# plot coastal lines:
plot(gadm, add = T)
You can use rasterVis package for that purpose:
# load needed librairies
library(rasterVis)
library(rgeos)
# open the data
salinity <- brick("data.nc", varname = "salinity")
# load coastal lines of Indonesia:
con <- url("http://biogeo.ucdavis.edu/data/gadm2/R/IDN_adm0.RData")
load(file = con)
close(con)
# clip the coastline to the study area
CP <- as(extent(salinity), "SpatialPolygons")
proj4string(CP) <- CRS(proj4string(gadm))
gadm <- gIntersection(gadm, CP, byid=TRUE)
# map
levelplot(subset(salinity, 1), margin = FALSE) +
layer(sp.polygons(gadm, fill='transparent', col='black'))
Related
I have a ncdf file for the whole world and I just want to extract and plot US.
our_nc_data <- nc_open("main_2010.nc")
print(our_nc_data)
lswt_array <- ncvar_get(our_nc_data, "o3")
image(lswt_array)
our_nc_data$dim$lon$vals -> lon
our_nc_data$dim$lat$vals -> lat
image(lon,lat, lswt_array)
library(maptools)
data(wrld_simpl)
plot(wrld_simpl,add=TRUE)
I have some code in R which does the following:
Uses lapply to bring in files in a set folder e.g. 1997 data
Makes file list into a brick - they are NetCDF files, so I've used brick function
Stacks the bricks into one raster stack of months for each year.
Calculate the mean from the stack
Crops the new mean raster to the Area of Interest (AOI).
I've got a working code, see below, but it is clunky and I feel could be better in one loop to then run through each year's folder (I have data from 1997 to 2018). Could anyone aid in streamlining this into a simple looped code I could run by changing the filepath? I've used loops a bit before but not from scratch.
# Packages:
library(raster)
library(parallel) # Check cores in PC
library(lubridate) # needed for lapply
library(dplyr) # ""
library(sf) # For clipping data
library(rgdal)
# ChlA
# Set file paths for input and outputs:
usingfp <- "/filepath/GIS/ChlA/1997/"
the_dir_ex <- "Data/CHL/1997"
# List all NETCDF files in folder:
CHL_1997 <- list.files(path = usingfp, pattern = "\\.nc$", full.names = TRUE,
recursive = FALSE)
# Make file list into brick
CHL_1997_brick <- lapply(CHL_1997,
FUN = brick,
the_dir = the_dir_ex)
# Stack bricks
s <- stack(CHL_1997_brick)
# Calculate mean from stack
mean <- calc(s, fun = mean, na.rm = T)
plot(mean)
# Load vector boundary to "crop" to
AOI <- readOGR("/filepath/AOI/AOI.shp")
plot(AOI,
main = "Shapefile imported into R - crop extent",
axes = TRUE,
border = "blue",
add = T)
# crop the raster using the vector extent
CHL_1997_mean <- crop(mean, AOI)
plot(CHL_1997_mean, main = "Cropped mean CHL - 1997")
# add shapefile on top of the existing raster
plot(AOI, add = TRUE)
Thanks very much.
Something like this should work
library(raster)
AOI <- shapefile("/filepath/AOI/AOI.shp")
path <- "/filepath/GIS/ChlA/"
years <- 1997:2018
for (yr in years) {
fp <- file.path(path, yr)
fout <- file.path(fp, paste0(year, ".tif"))
print(fout); flush.console()
# if (file.exists(fout)) next
files <- list.files(path=fp, pattern="\\.nc$", full.names=TRUE)
b <- lapply(files, brick)
s <- stack(b)
s <- mean(s)
s <- crop(s, AOI, filename=fout) #, overwrite=TRUE)
}
Notes:
mean(s) is more efficient than calc(s, mean)
If the AOI is relatively small, it can be more efficient to first
use crop, then mean (and then use writeRaster)
You can also use terra like this:
library(terra)
AOI <- vect("/filepath/AOI/AOI.shp")
path <- "/filepath/GIS/ChlA/"
years <- 1997:2018
for (yr in years) {
fp <- file.path(path, year)
fout <- file.path(fp, paste0(year, ".tif"))
print(fout); flush.console()
# if (file.exists(fout)) next
files <- list.files(path=fp, pattern="\\.nc$", full.names=TRUE)
r <- rast(files)
s <- mean(r)
s <- crop(s, AOI, filename=fout) #, overwrite=TRUE)
}
R Programming Language (New to this)
I am attempting to loop through a number of tiled rasters that have been output by splitRaster. During the loop I want to carry out some processes on each raster.
But the following code throws an error.
library(ForestTools)
library(raster)
library(sp)
library(rgdal)
library(SpaDES)
rm(list = ls())
tmpdir <- file.path(tempdir(), "splitRaster")
lin <- function(x){x * 0.1 + 0.6}
inCHM <- raster("input raster path and name.tif")
split <- splitRaster(inCHM, 5, 5, c(0.05, 0.05), tmpdir)
files <- list.files(path=tmpdir, pattern="*.grd", full.names=FALSE, recursive=FALSE)
file.names <- dir(tmpdir, pattern ="*.grd")
for(file.names in files ){
name <- file.names
ttops <- vwf(name, winFun = lin, minHeight = 5)
writeOGR(ttops, "output folder", name, driver = "ESRI Shapefile")
}
and this is the error
[1] "Xrastername_tile1.grd"
Error in CRS(x) :
PROJ4 argument-value pairs must begin with +: Xrastername_tile1.grd
More to the problem (24/7/2020),
I have removed the loop for trouble shooting instead just choosing one of the splitRasters outputs that would be used in the loop ie files[[3]]
When I run the following code the error is the same;
library(ForestTools)
library(raster)
library(sp)
library(rgdal)
library(SpaDES)
rm(list = ls())
# set temp directory
tmpdir <- "C:\\R-Test\\Temp_Output"
# get raster
r <- raster("C:\\Lidar\\grid_treeheight_max_1m_nofill.tif")
# define projection
projection(r) <- "+proj=utm +zone=50 +south +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs"
# split raster brick
y <- splitRaster(r, 8, 8, c(0.05, 0.05), tmpdir)
# Get the complete file locations with full.names = T
files <- list.files(path=tmpdir, pattern="*.grd", full.names=FALSE, recursive=FALSE)
tmpfile <- paste(tmpdir, "\\", files[[3]], sep="")
lin <- function(x){x * 0.06 + 0.6}
ttops <- vwf(tmpfile, winFun = lin, minHeight = 5)
This is the error
Error in CRS(x) :
PROJ4 argument-value pairs must begin with +: D:\R-Test\Temp_Output\Xgrid_treeheight_max_1m_nofill_tile11.grd
When I run the following code using one of the splitRaster outputs (files[[3]]) from the above code it runs error free and I am able to plot ttops.
rm(list = ls())
# set temp directory
tmpdir <- "D:\\R-Test\\Temp_Output"
# get raster
r <- raster("D:\\R-Test\\Temp_Output\\Xgrid_treeheight_max_1m_nofill_tile11.grd")
lin <- function(x){x * 0.06 + 0.6}
ttops <- vwf(r, winFun = lin, minHeight = 5)
Why is the PROJ4 error occurring?
This seems to be the error that is causing the loop to fail?
I think the problem is that you are trying to feed the vwf function with the file name instead of a raster object. I would also recommend using lapply instead of for for the loop. Here is a code that should work
library(raster)
library(ForestTools)
library(rgdal)
# Get the complete file locations with full.names = T
files <- list.files(path=tmpdir, pattern="*.grd", full.names=T, recursive=FALSE)
# Loop over each item of the list, i.e., each raster
lapply(files, function(x){
# Load the image as raster
image <- raster(x)
# Calculate vwf (I added a dummy function for winFun)
ttops <- vwf(image, winFun = function(x){x * 0.06 + 0.5}, minHeight = 5)
# Write the file with the name of each raster
writeOGR(ttops, "output_dir", names(x), driver = "ESRI Shapefile")
})
I have converted U and V component of wind to wind direction and magnitude. But didn't able to map this data using levelplot.
library(raster)
library(rgdal)
library(rasterVis)
library(lattice)
library(grid)
Ucomplist <- list.files(path = "F:/ShareBoth/yearly_variable_data/rasters/Ucomp_annual/Ucomp_annual/", full.names = TRUE)
length(Ucomplist)
U <- brick(Ucomplist)
Vcomplist <- list.files(path = "F:/ShareBoth/yearly_variable_data/rasters/Vcomp_annual/Vcomp_annual/", full.names = TRUE)
length(Vcomplist)
V <- brick(Vcomplist)
wd <- (180/pi)*(atan2(U,V))
ws <- sqrt(U^2+V^2)
data link
https://drive.google.com/drive/folders/1PwABGUDBVUWi50Vfn9pmC-Dyjkpmtyny?usp=sharing
expected output:
thanks in advance
I'm looking for a way to re-order a set of Formal Class Spatial Polygons using
I'm using US Census data (Limited to Texas) and want to create 33 polygons out of different county combinations.
library(tmap)
library(maptools)
library(ggplot2)
library(rgeos)
library(sp)
library(mapdata)
library(rgdal)
library(raster)
# Download the map of texas and get the LMAs boundaries
# Download shape
f <- tempfile()
download.file("http://www2.census.gov/geo/tiger/GENZ2010/gz_2010_us_050_00_20m.zip", destfile = f)
unzip(f, exdir = ".")
US <- read_shape("gz_2010_us_050_00_20m.shp")
# Select only Texas
Texas <- US[(US$STATE %in% c("48")),]
# Load the LMA append data
LMAs = read.table('LMA append data.csv',header=T, sep=',')
# Append LMA data to Texas shape
Texas$FIPS <- paste0(Texas$STATE, Texas$COUNTY)
Texas <- append_data(Texas, LMAs, key.shp = "FIPS", key.data = "FIPS")
Texas <- Texas[order(Texas$LMA),]
# Create shape object with LMAs polygons
Texas_LMA <- unionSpatialPolygons(Texas, IDs=Texas$LMA)
I've tried converting Texas_LMA into a SpatialPolygonsDataFrame with
# Create shape object with LMAs polygons
Texas_LMA <- unionSpatialPolygons(Texas, IDs=Texas$LMA)
spp <- SpatialPolygonsDataFrame(Texas_LMA,data=matrix(1:33,nrow=33,ncol=1))
But that hasn't worked for me.
Your question is not very clear. But I think this is what you are after:
library(raster)
f <- tempfile() download.file("http://www2.census.gov/geo/tiger/GENZ2010/gz_2010_us_050_00_20m.zip", destfile = f)
unzip(f, exdir = ".")
US <- shapefile("gz_2010_us_050_00_20m.shp")
Texas <- US[(US$STATE %in% c("48")),]
LMAs = read.csv('LMA append data.csv')
Texas$FIPS <- paste0(Texas$STATE, Texas$COUNTY)
You did not provide the LMA data, so guessing a bit from here:
Texas <- merge(Texas, LMAs, by="FIPS")
Texas_LMA <- aggregate(Texas, by='LMA')
shapefilename[order(shapefilename$column_name),]