{"id":1626,"date":"2018-06-26T14:05:51","date_gmt":"2018-06-26T12:05:51","guid":{"rendered":"https:\/\/blogs.fu-berlin.de\/reseda\/?page_id=1626"},"modified":"2018-09-25T11:09:59","modified_gmt":"2018-09-25T09:09:59","slug":"preprocess-landsat-exercise","status":"publish","type":"page","link":"https:\/\/blogs.fu-berlin.de\/reseda\/preprocess-landsat-exercise\/","title":{"rendered":"Preprocess L8 Exercise"},"content":{"rendered":"

1) Commenting on scripts is extremely useful, especially if you want to look at it later and understand what’s going on. Test your understanding of the script for pre-processing a single L8 scene shown in the previous section. Copy the following code into the script window of R-Studio. For each line, try to give a brief explanation of what is being done in the next line of code! (Explanation of the first line is given)<\/p>\n

\r\n# load the raster library in the current session\r\n# (needed for rasterstack and writeRaster)\r\nlibrary(raster)\r\n\r\n#\r\nproduct <- "\/media\/sf_exchange\/landsatdata\/LC081930232017060201T1-SC20180613160412.tar.gz"\r\n\r\n#\r\nproductname <- substr(product, 1, nchar(product) - 7) \r\n\r\n#\r\nuntar(product, exdir = productname)\r\n\r\n#\r\nproductfiles <- list.files(productname, full.names = TRUE)\r\n\r\n#\r\nbands <- c(grep('band1', productfiles, value=TRUE),\r\n           grep('band2', productfiles, value=TRUE),\r\n           grep('band3', productfiles, value=TRUE),\r\n           grep('band4', productfiles, value=TRUE),\r\n           grep('band5', productfiles, value=TRUE),\r\n           grep('band6', productfiles, value=TRUE),\r\n           grep('band7', productfiles, value=TRUE)\r\n           ) \r\n\r\n#\r\nrasterstack <- stack( bands )\r\n\r\n#\r\nwriteRaster(rasterstack, \r\n            paste0(productname, ".tif"), \r\n            format = "GTiff",\r\n            overwrite = TRUE\r\n            )\r\n\r\n#\r\nunlink(productname, recursive=TRUE)\r\n\r\n#\r\nmakeOVR <- paste0("gdaladdo -ro ", productname, ".tif 2 4 8 16")\r\nsystem( makeOVR )\r\n<\/pre>\n
Done? Compare it with the solution:<\/p>\n
\r\n# load the raster library in the current session\r\n# (needed for rasterstack and writeRaster)\r\nlibrary(raster)\r\n\r\n# define file path of a single L8 dataset \r\nproduct <- "\/media\/sf_exchange\/landsatdata\/LC081930232017060201T1-SC20180613160412.tar.gz"\r\n\r\n# get the export folder for decompression by deleting suffix (.tar.gz) \r\nproductname <- substr(product, 1, nchar(product) - 7) \r\n\r\n# decompress and save to export folder \r\nuntar(product, exdir = productname)\r\n\r\n# create a vector of all names of files in decompressed folder\r\nproductfiles <- list.files(productname, full.names = TRUE)\r\n\r\n# search for individual bands inside file vector\r\nbands <- c(grep('band1', productfiles, value=TRUE),\r\n           grep('band2', productfiles, value=TRUE),\r\n           grep('band3', productfiles, value=TRUE),\r\n           grep('band4', productfiles, value=TRUE),\r\n           grep('band5', productfiles, value=TRUE),\r\n           grep('band6', productfiles, value=TRUE),\r\n           grep('band7', productfiles, value=TRUE)\r\n           ) \r\n\r\n# create a rasterstack of the band selection\r\nrasterstack <- stack( bands )\r\n\r\n# write the rasterstack to hard drive\r\nwriteRaster(rasterstack, \r\n            paste0(productname, ".tif"), \r\n            format = "GTiff",\r\n            overwrite = TRUE\r\n            )\r\n\r\n# delete the uncompressed folder in order to save disc space\r\nunlink(productname, recursive=TRUE)\r\n\r\n# create pyramid layers for faster visualization\r\nmakeOVR <- paste0("gdaladdo -ro ", productname, ".tif 2 4 8 16")\r\nsystem( makeOVR )\r\n<\/pre>\n
2) Download any Landsat-8 Level-1 dataset using the USGS EarthExplorer. Modify the code given in the previous task so that you create and store a datastack of all the spectral channels available in this Level-1 dataset!<\/p>\n
\r\nlibrary(raster)\r\n \r\nproduct <- "\/media\/sf_exchange\/landsatdata\/LC081930232017060201T1-SC20180613160412.tar.gz"\r\n \r\nproductname <- substr(product, 1, nchar(product) - 7) \r\n \r\nuntar(product, exdir = productname)\r\n \r\nproductfiles <- list.files(productname, full.names = TRUE)\r\n \r\nbands <- c(grep('band1', productfiles, value=TRUE),\r\n           grep('band2', productfiles, value=TRUE),\r\n           grep('band3', productfiles, value=TRUE),\r\n           grep('band4', productfiles, value=TRUE),\r\n           grep('band5', productfiles, value=TRUE),\r\n           grep('band6', productfiles, value=TRUE),\r\n           grep('band7', productfiles, value=TRUE),\r\n           grep('band8', productfiles, value=TRUE),\r\n           grep('band9', productfiles, value=TRUE),\r\n           grep('band10', productfiles, value=TRUE),\r\n           grep('band11', productfiles, value=TRUE)\r\n           ) \r\n \r\nrasterstack <- stack( bands )\r\n \r\nwriteRaster(rasterstack, \r\n            paste0(productname, ".tif"), \r\n            format = "GTiff",\r\n            overwrite = TRUE\r\n            )\r\n \r\nunlink(productname, recursive=TRUE)\r\n \r\nmakeOVR <- paste0("gdaladdo -ro ", productname, ".tif 2 4 8 16")\r\nsystem( makeOVR )\r\n<\/pre>\n
<\/br><\/br><\/p>\n
\n
\n