Extracting values from multiple raster to CSV using R

Question

I have multiple raster TIF files. I'm using R and want to extract a cell's attribute value from all rasters based on an latitude and longitude input, and saved in a single CSV file. The output should be formatted as follows:

      Lat          Long       Value*       Value**
     20.15        77.12        12            20

* denotes attribute values from raster 1.
** denotes attribute values from raster 2.

Can anyone help me in this?

Answer 1

EDIT 2: I provide a shorter version based on extract function from the raster package.

library(raster)
library(sp) # used to create a SpatialPoint object

# LOAD RASTERS INTO A LIST OBJECT. 
tmp <- lapply(list.files("D:/rasters", pattern = ".tif$", full.names = TRUE), raster)

# A DATA FRAME WITH THE FOLLOWING STRUCTURE IS REQUIRED
coords <- data.frame("lat" = c(-2.2, -13.76, 4.47), "lon" = c(5.97, 10.57, 8.7))

# NEW CODE STARTS HERE
pts <- SpatialPoints(coords = coords, 
              proj4string = CRS("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs "))

# THE NEXT LINE PROVIDES THE SAME OUTPUT AS THE FOLLOWING LONG CODE
as.data.frame(cbind(coords, do.call("rbind", lapply(tmp, extract, pts))))

I provide a generalized answer by making usage of a raster library functionality. It can be used to process multiple raster files and multiple lat-lon pairs.

The main idea is to use cellFromXY to get the cell index for a specific lat-lon pair. Then just extract the value using r[cellIndex], when r is a raster object.

This is given for a data frame with one row - i.e. only one pair of lat-lon, but you can easily wrap it with another lapply combined with rbind to iterate it over multiple lat-lon pairs.

EDIT: now you can run the code using multiple lat-lon points. Note that the input data.frame structure should be kept.

library(magrittr) # I used piping in my answer (%>%)
library(raster)   # raster functionality in r

# Assuming my .tif files are in this path: "D:/rasters"    

# LOAD RASTERS INTO A LIST OBJECT. 
tmp <- lapply(list.files("D:/rasters", pattern = ".tif$", full.names = TRUE), raster)

# A DATA FRAME WITH THE FOLLOWING STRUCTURE IS REQUIRED
coords <- data.frame("lat" = c(-2.2, -13.76, 4.47), "lon" = c(5.97, 10.57, 8.7))

# RUN THE FOLLOWING TO GET A MATRIX WITH VALUES
cellData <- lapply(tmp, function(r) {
  apply(coords, MARGIN = 1, FUN = function(row) {
    # as.matrix(coords[row, c("lat", "lon")]) # print(row)
    cellIndex <- cellFromXY(r, row) # gives cell Index for lat/lon pair
    r[cellIndex]
  })
}) %>% do.call("cbind", .)

# BIND MATRIX AS A DATA FRAME
output <- as.data.frame(cbind(coords, cellData))

Finally my result for 3 rasters and 3 points looks like this:

Answer 2

Here is how I would do it. This assumes that the 2 rasters have exactly the same number of pixels and exactly the same extent

library(raster)
r1<-raster("MyRasterName1.tiff")
r2<-raster("MyRasterName2.tiff")

# Get the extent of each raster
r1Extent<-extent(r1)
r2Extent<-extent(r2)

# Extract each pixel value for r1 into a dataframe
r1Extraction<-extract(r1,r1Extent, df=TRUE, cellnumbers=TRUE)
# create a data frame with the coordinates of each cell.
r1Coords<-as.data.frame(xyFromCell(r1,r1Extraction[,2]))
# bind the coordinates with the values of the cell
r1Final<-cbind(r1Coords,r1Extraction[,3])

# Extract each pixel value for r2 into a data frame
r2Extraction<-extract(r2, r2Extent, df=TRUE, cellnumbers=TRUE)

# bind the extraction to the r1Final data frame.
finalData<-cbind(r1Final, r2Extraction[,3]

# change the column names to what you want.
colnames(myFinalData)<-c("X","Y","R1","R2")

# Save as a CSV
write.csv(finalData, file="myFileName.csv", row.names = FALSE)