Compose true color Landsat 7 images using R

If you are familiar with Landsat 7 (1999 - 2013), you know that there was failure with the Scan Line Corrector instrument early in the mission deployment. The end result is that a sizable portion (~22 %) of each “scene” has been lost. People interested in creating true color images without these missing data gaps might find themselves at the USGS page describing how to fill gaps for display.

landsat

However, after reading the page you might think that the only solutions for gap-filling involve using very expensive proprietary software (ERDAS, Photoshop) or paying for corrected imagery from a Landsat business partner. Not having access to these software programs, I unsuccessfully attempted to use the Dust-and-Scratches solution albeit with open-source imaging programs. After quite a bit of struggling I discoved an easy alternative which I will now share.

First we need to acquire some Landsat data. I found this guide by Robert Simmon to be an excellent introduction to the topic. (On a side-note, the landsat-util program looks excellent. It is too bad it only provides access to Landsat 8 data.)

In this case we have downloaded our compressed achive to the /home folder. Landsat 7 data archives have the following file/folder structure and for the purposes of creating true color images we are only concerned with bands 1-3. One important thing to note is the presence of a gap_mask folder. The tif files within the gap_mask archives contain the missing data from the top level band files.

    LE70150432010.tar.gz
    │   LE70150432010_B1.TIF
    │   LE70150432010_B2.TIF
    │   LE70150432010_B3.TIF
    │
    └───gap_mask
        ├───LE70150432010_GM_B1.TIF.gz
        │   │   LE70150432010_GM_B1.TIF
        ├───LE70150432010_GM_B2.TIF.gz
        │   │   LE70150432010_GM_B2.TIF
        ├───LE70150432010_GM_B3.TIF.gz
        │   │   LE70150432010_GM_B3.TIF

The following R code chunk loops through each band/mask combination and uses the gdal_fillnodata.py script (ships with gdal by default) to replace missing data in each band with the corresponding data in the mask file. Next, the resulting rasters are cropped according to a custom defined extent. Finally, the bands are combined and plotted using the plotRGB function.

Before running this workflow on your own landsat 7 data ensure that you have gdal installed and available to the base::system command. You can check this by running gdal-config --version from the command line. Also make sure that you have the rgdal and raster packages installed.

    untar(paste0("~/LE70260412007180EDC00.tar.gz"), exdir = "landsat")
    
    tifs <- list.files("landsat", pattern = "*.TIF$",
      include.dirs = TRUE, full.names = TRUE)[1:3]
    ctifs<-paste0(unlist(strsplit(tifs,".TIF")), "_f", ".TIF")
    masks <- list.files("landsat/gap_mask", include.dirs = TRUE, full.names = TRUE)[1:3]
    
    library(raster)
    library(rgdal)
            
    for(i in 1:length(tifs)){
      system(paste("gdal_fillnodata.py -mask", paste0("/vsigzip/", masks[i]), "-of GTiff", tifs[i], ctifs[i]))
      }
            
    rstack <- raster::stack(ctifs)
            
    #raster::drawExtent()
    extent <- raster::extent(625508, 673853, 3072252, 3096110)
    rstack <- raster::crop(rstack, extent)
              
    raster::plotRGB(rstack,r=3,g=2,b=1)
    rect(extent[1], extent[3], extent[2], extent[4], lwd = 1.5)
    
    #file.remove(list.files("landsat", include.dirs = TRUE, full.names = TRUE,
      recursive = TRUE))

landsat